Journal Paper

• Cunyuan Ji, Kengo Oshima, Takumi Urata, Fumikazu Kimura, Keiko Ishii, Takeshi Uehara, Kenji Suzuki, Saori Takeyama, Masahiro Yamaguchi. Transformation from Hematoxylin-and-eosin Staining to Ki-67 Immunohistochemistry Digital Staining Images Using Deep Learning: Experimental Validation on the Labeling Index, Journal of Medical Imaging, Vol. 11, Issue 4, 047501, July 2024.
• Samala R. K., Drukker K., Shukla-Dave A., Chan H. P., Sahiner B., Petrick N., Greenspan H., Mahmood U., Summers R. M., Tourassi G., Deserno T. M., Regge D., Nappi J. J., Yoshida H., Huo Z., Chen Q., Vergara D., Cha K. H., Mazurchuk R., Grizzard K. T., Huisman H., Morra L., Suzuki K., Armato III S. G., Hadjiiski L.. AI and machine learning in medical imaging: key points from development to translation, BJR Artificial Intelligence, Vol. 1, No. 1, Apr. 2024.
• Mahmood U., Shukla-Dave A., Chan H. P., Drukker K., Samala R. K., Chen Q., Vergara D., Greenspan H., Petrick N., Sahiner B., Huo Z., Summers R. M., Cha K. H., Tourassi G., Deserno T. M., Grizzard K. T., Nappi J. J., Yoshida H., Regge D., Mazurchuk R., Suzuki K., Morra L., Huisman H., Armato, III S. G., Hadjiiski L.. Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing, BJR Artificial Intelligence, Vol. 1, No. 1, Mar. 2024.
• Pavarut S., Preedanan W., Kumazawa I., Suzuki K., Kobayashi M., Tanaka H., Ishioka J., Matsuoka Y., Fujii Y.. Improving Kidney Tumor Classification With Multi-Modal Medical Images Recovered Partially by Conditional CycleGAN, IEEE Access, Vol. 11, pp. 146250-146261, Dec. 2023.
• Wahyu Rahmaniar, Kenji Suzuki, Ting-Lan Lin. Auto-CA: Automated Cobb Angle Measurement Based on Vertebrae Detection for Assessment of Spinal Curvature Deformity, IEEE Transactions on Biomedical Engineering, Vol. 71, no. 2, pp. 640-649, Sept. 2023.
• Tomoyuki Shishido, Yasuhiro Ono, Itsuo Kumazawa, Ichiro Iwai, kenji suzuki. Artificial intelligence model substantially improves stratum corneum moisture content prediction from visible-light skin images and skin feature factors, Skin Research and Technology, Vol. 29, Issue 8, July 2023.
• Wongsakorn Preedanan, Kenji Suzuki, Toshiaki Kondo, Masaki Kobayashi, Hajime Tanaka, Junichiro Ishioka, Yoh Matsuoka, Yasuhisa Fujii, Itsuo Kumazawa. Urinary Stones Segmentation in Abdominal X-Ray Images Using Cascaded U-Net Pipeline with Stone-Embedding Augmentation and Lesion-Size Reweighting Approach, IEEE Access, vol. 11, pp. 25702-25712, Mar. 2023.  Official location  
• Lubomir Hadjiiski, Kenny Cha, Heang-Ping Chan, Karen Drukker, Lia Morra, Janne J. Näppi, Berkman Sahiner, Hiroyuki Yoshida, Quan Chen, Thomas M. Deserno, Hayit Greenspan, Henkjan Huisman, Zhimin Huo, Richard Mazurchuk, Nicholas Petrick, Daniele Regge, Ravi Samala, Ronald M. Summers, Kenji Suzuki, Georgia Tourassi, Daniel Vergara, Samuel G. Armato III. AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging, Medical Physics, Vol. 50, Issue 2, e1-e24, Dec. 2022.
• Wongsakorn Preedanan, Kenji Suzuki, Kondo T., Kobayashi M., Tanaka H., Ishioka J., Matsuoka Y., Fujii Y., Itsuo Kumazawa. Improvement of Urinary Stone Segmentation Using GAN-Based Urinary Stones Inpainting Augmentation, IEEE Access, vol. 10, pp. 115131-115142, Oct. 2022.
• Kobayashi M., Ishioka J., Matsuoka Y., Fukuda Y., Kohno Y., Kawano K., Morimoto S., Muta R., Fujiwara M., Kawamura N., Okuno T., Yoshida S., Yokoyama M., Suda R., Saiki R., Suzuki K., Kumazawa I., Fujii Y.. Computer-aided diagnosis with a convolutional neural network algorithm for automated detection of urinary tract stones on plain X-ray, BMC Urology, Vol. 21, Aug. 2021.
• Kenji Suzuki. 深層学習による医用画像診断支援, BIO Clinica, 北隆館, Vol. 36, No. 7, pp. 92-94, July 2021.
• Kenji Suzuki. Artificial Intelligence for Virtual Medical Imaging for Accurate Diagnosis, Video Proceedings of Advanced Materials, Vol. 2, May 2021.
• Kenji Suzuki. スモールデータ深層学習とその医用画像処理・診断支援への応用, 医学のあゆみ, Vol. 274, No. 9, pp. 737-742, Aug. 2020.
• Martínez-García M., Zhang Y., Kenji Suzuki, Zhang Y.. Deep Recurrent Entropy Adaptive Model for System Reliability Monitoring, IEEE Transactions on Industrial Informatics, Vol. 17, No. 2, pp. 839-848, 2020.
• Zarshenas A., Liu J., Forti P., Kenji Suzuki. Separation of bones from soft tissue in chest radiographs: Anatomy-specific orientation-frequency-specific deep neural network convolution, Medical Physics, Vol. 46, No. 5, pp. 2232-2242, May 2019.  Official location  
• Shi, Z., Hao, H., Zhao, M., Feng, Y., He, L., Wang, Y., Kenji Suzuki. A deep CNN based transfer learning method for false positive reduction, Multimedia Tools and Applications, Vol. 78, No. 1, pp. 1017-1033, Jan. 2019.  Official location  
• 平野靖, 伊藤貴佳, 橋本典明, 木戸尚治, Kenji Suzuki. 胸腹部コンピューター支援診断におけるMTANN深層学習, Medical Imaging Technology, vol. 35, no. 4, pp. 194-199, Sept. 2017.
• Kenji Suzuki. Survey of Deep Learning Applications to Medical Image Analysis, Medical Imaging Technology, Vol. 35, No. 4, pp. 212-226, Sept. 2017.
• Kenji Suzuki. Overview of deep learning in medical imaging, Radiological Physics and Technology, Vol. 10, No. 3, pp. 257-273, Sept. 2017.
• Kenji SUZUKI. Machine Learning in Medical Imaging Before and After Introduction of Deep Learning, Medical Imaging and Information Sciences, Vol. 34, No. 2, pp. 14-24, June 2017.
• Ayman El-Baz, Georgy Gimel’farb, Kenji Suzuki. Special issue: Machine Learning Applications in Medical Image Analysis, Computational and Mathematical Methods in Medicine, Hindawi, Vol. 2017, Apr. 2017.  Official location  
• Chen, Y., Chan, A.B., Lin, Z., Wang, G., Kenji Suzuki. Efficient tree-structured SfM by RANSAC generalized Procrustes analysis, Computer Vision and Image Understanding, Vol. 157, pp. 179-189, Apr. 2017.  Official location  
• Kenji Suzuki, Luping Zhou, Qian Wang. Special issue: Machine Learning in Medical Imaging, Pattern Recognition, Elsevier, Vol. 63, pp. 740, Mar. 2017.  Official location  
• Huynh, H.T., Le-Trong, N., Bao, P.T., Oto, A., Kenji Suzuki. Fully automated MR liver volumetry using watershed segmentation coupled with active contouring, International Journal of Computer Assisted Radiology and Surgery, Vol. 12, No. 2, pp. 235-243, Feb. 2017.  Official location  
• He, L., Zhao, X., Yao, B., Yang, Y., Chao, Y., Shi, Z., Kenji Suzuki. A combinational algorithm for connected-component labeling and Euler number computing, Journal of Real-Time Image Processing, Vol. 13, No. 4, pp. 703-712, 2017.  Official location  
• Tajbakhsh, N., Kenji Suzuki. Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs, Pattern Recognition, Vol. 63, pp. 476-486, 2017.  Official location  
• Zarshenas, A., Kenji Suzuki. Binary coordinate ascent: An efficient optimization technique for feature subset selection for machine learning, Knowledge-Based Systems, Vol. 110, pp. 191-201, Oct. 2016.  Official location  
• Gonzalo Pajares Martinsanz, Philip Morrow, Kenji Suzuki. Special issue: Image and Video Processing in Medicine, Journal of Imaging, MDPI, Oct. 2016.  Official location  
• Yi-Xiang Wang, Yong E. Chung, Weibo Cai, Kenji Suzuki. Special issue: Advances in Translational Cancer Imaging: Opportunities and Challenges, BioMed Research International, Hindawi, Vol. 2016, Aug. 2016.  Official location  
• Chen, S., Zhong, S., Yao, L., Shang, Y., Kenji Suzuki. Enhancement of chest radiographs obtained in the intensive care unit through bone suppression and consistent processing, Physics in Medicine and Biology, Vol. 61, No. 6, pp. 2283-2301, Mar. 2016.  Official location  
• Sihai, Y., Xu, J., Kenji Suzuki. Density Index: Extension of Shape Index in Describing Local Intensity Variations in a 3D Image, Journal of Computer-Aided Design & Computer Graphics, Vol. 28, no. 7, pp. 1152-1159, 2016.
• Shi, Z., Ma, J., Zhao, M., Liu, Y., Feng, Y., Zhang, M., He, L., Kenji Suzuki. Many Is Better Than One: An Integration of Multiple Simple Strategies for Accurate Lung Segmentation in CT Images, BioMed Research International, Vol. 2016, pp. 13 pages, 2016.  Official location  
• Shi Z., Ma J., Feng L., He L., Kenji Suzuki. Evaluation of MTANNs for eliminating false-positive with different computer aided pulmonary nodules detection software, Pakistan Journal of Pharmaceutical Sciences, Vol. 28, No. 6, pp. 2311-2316, Nov. 2015.
• Epstein M. L., Obara P. R., Chen Y., Liu J., Zarshenas A., Makkinejad N., Dachman A. H., Kenji Suzuki. Quantitative radiology: automated measurement of polyp volume in computed tomography colonography using Hessian matrix-based shape extraction and volume growing, Quantitative imaging in medicine and surgery, Vol. 5, No. 5, pp. 673-684, Sept. 2015.
• Shi, Z., Xu, B., Zhao, M., Zhao, J., Wang, Y., Liu, Y., Zhang, M., He, L., Kenji Suzuki. A joint ROI extraction filter for computer aided lung nodule detection, Bio-Medical Materials and Engineering, Vol. 26, No. s1, pp. S1491-S1499, Aug. 2015.  Official location  
• Dai, P., Luo, H., Sheng, H., Zhao, Y., Li, L., Wu, J., Zhao, Y., Kenji Suzuki. A new approach to segment both main and peripheral retinal vessels based on gray-voting and Gaussian mixture model, PLoS ONE, Vol. 10, No. 6, e0127748, June 2015.  Official location  
• Kenji Suzuki. Special issue: Machine Learning in Medical Imaging, Computerized Medical Imaging and Graphics, Elsevier, Vol. 41, pp. 125, Apr. 2015.  Official location  
• Shi, Z., Si, C., Zhao, M., He, L., Zhang, M., Kenji Suzuki. An automatic method for lung segmentation in thin slice computed tomography based on random walks, Journal of Medical Imaging and Health Informatics, Vol. 5, No. 2, pp. 303-308, Apr. 2015.  Official location  
• Wang Y. X., Loffroy R., Arora R., Kenji Suzuki, Lee C. H., Chung H. W., Oei E. H., Winston G. P., Ng C. K.. Relative income of clinical faculty members vs. science faculty members in university settings-a short survey of France, Hong Kong, India, Japan, South Korea, The Netherlands, Taiwan, UK, and USA, Quantitative Imaging in Medicine and Surgery, Vol. 4, No. 6, pp. 500-501, Dec. 2014.
• Fei Zuo, Jungong Han, Pingkun Yan, Hans van Assen, Kenji Suzuki. Special issue: Advanced Computing for Image-Guided Intervention, Elsevier, Vol. 144, pp. 596, Nov. 2014.  Official location  
• Yi-Xiang J Wang, Jing-Shan Gong, Kenji Suzuki, Sameh K Morcos. Evidence based imaging strategies for solitary pulmonary nodule, Journal of Thoracic Disease, Vol. 6, No. 7, pp. 872-887, July 2014.  Official location  
• He, L., Zhao, X., Chao, Y., Kenji Suzuki. Configuration-transition-based connected-component labeling, IEEE Transactions on Image Processing, Vol. 23, No. 2, pp. 943-951, Feb. 2014.  Official location  
• Huynh, H.T., Karademir, I., Oto, A., Kenji Suzuki. Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation, American Journal of Roentgenology, Vol. 202, No. 1, pp. 152-159, Jan. 2014.  Official location  
• Zhenghao Shi, Chunjiao Si, Yaning Feng, Lifeng He, Kenji Suzuki. A new method based on MTANNs for cutting down false-positives:An evaluation on different versions of commercial pulmonary nodule detection CAD software, Bio-Medical Materials and Engineering,, vol. 24, no. 6, pp. 2839-2846, 2014.  Official location  
• Chen S., Kenji Suzuki. Separation of bones from chest radiographs by means of anatomically specific multiple massive-training ANNs combined with total variation minimization smoothing, IEEE Transactions on Medical Imaging, Vol. 33, No. 2, pp. 246-257, Oct. 2013.  Official location  
• Pingkun Yan, Kenji Suzuki, Fei Wang, Dinggang Shen. Special issue: Machine Learning in Medical Imaging, Machine Vision and Applications, Springer, Vol. 24, Issue 7, Oct. 2013.  Official location  
• Jian-Wu Xu, Kenji Suzuki. Max-AUC feature selection in computer-aided detection of polyps in CT colonography, IEEE Journal of Biomedical and Health Informatics, Vol. 18, No. 2, pp. 585-593, Aug. 2013.  Official location  
• Li-Feng He, Yu-Yan Chao, Kenji Suzuki. An algorithm for connected-component labeling, hole labeling and euler number computing, Journal of Computer Science and Technology, Vol. 28, No. 3, pp. 468-478, May 2013.  Official location  
• Shi, Z., Zhao, M., He, L., Wang, Y., Zhang, M., Kenji Suzuki. A Computer Aided Pulmonary Nodule Detection System Using Multiple Massive Training SVMs, Applied Mathematics & Information Sciences, Vol. 7, pp. 1165-1172, May 2013.  Official location  
• Kenji Suzuki. Machine learning in computer-aided diagnosis of the thorax and colon in CT: A survey, IEICE Transactions on Information and Systems, Vol. E96-D, No. 4, pp. 772-783, Apr. 2013.  Official location  
• Chen, S., Kenji Suzuki. Computerized detection of lung nodules by means of 'virtual dual-energy' radiography, IEEE Transactions on Biomedical Engineering, Vol. 60, No. 2, pp. 369-378, Feb. 2013.  Official location  
• El-Baz A., Beache G. M., Gimel'farb G., Kenji Suzuki, Okada K., Elnakib A., Soliman A., Abdollahi B.. Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies, International Journal of Biomedical Imaging, Vol. 2013, pp. 46 pages, Jan. 2013.  Official location  
• Yu, Q., He, L., Nakamura, T., Chao, Y., Kenji Suzuki. A mutual-information-based global matching method for chest-radiography temporal subtraction, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 16, No. 7, pp. 841-850, Nov. 2012.  Official location  
• Ayman El-Baz, Garth M. Beache, Georgy Gimel'farb, Kenji Suzuki, Kazunori Okada. Special issue: Lung Imaging Data Analysis, Hindawi, Nov. 2012.  Official location  
• Kenji Suzuki. A review of computer-aided diagnosis in thoracic and colonic imaging, Quantitative Imaging in Medicine and Surgery, Vol. 2, pp. 163-176, Sept. 2012.
• Kenji Suzuki. Special Issue: Machine Learning for Medical Imaging 2012, Algorithms, MDPI, Sept. 2012.  Official location  
• Shi Z., Li L., Zhao M., He L., Wang Y., Zhang M., Kenji Suzuki. Sparse field snake model: A novel active contour model used for lung segmentation on chest radiographs, ICIC Express Letters, Part B: Applications, Vol. 3, No. 4, pp. 777-783, Aug. 2012.  Official location  
• Shi, Z., Zhao, M., Wang, Y., He, L., Kenji Suzuki, Jin, C., Zhang, M.. Hessian-log: A novel dot enhancement filter, ICIC Express Letters, Part B: Applications, Vol. 6, No. 8, pp. 1987-1992, Aug. 2012.  Official location  
• Shi, Z., Li, L., Kenji Suzuki, Wang, Y., He, L., Jin, C., Zhang, M.. A new computer aided detection system for pulmonary nodule detection in chest radiography, Advanced Science Letters, Vol. 11, No. 1, pp. 536-541, May 2012.  Official location  
• Kenji Suzuki. Pixel-based machine learning in medical imaging, International Journal of Biomedical Imaging, Vol. 2012, Feb. 2012.  Official location  
• Liao S., Penney B.C., Zhang H., Kenji Suzuki, Pu Y.. Prognostic Value of the Quantitative Metabolic Volumetric Measurement on 18F-FDG PET/CT in Stage IV Nonsurgical Small-cell Lung Cancer, Academic Radiology, Vol. 19, No. 1, pp. 69-77, Jan. 2012.  Official location  
• He, L., Chao, Y., Kenji Suzuki. A new first-scan method for two-scan labeling algorithms, IEICE Transactions on Information and Systems, Vol. E95-D, No. 8, pp. 2142-2145, 2012.  Official location  
• Hori, M., Kenji Suzuki, Epstein, M.L., Baron, R.L.. Computed tomography liver volumetry using 3-dimensional image data in living donor liver transplantation: Effects of the slice thickness on the volume calculation, Liver Transplantation, Vol. 17, No. 12, pp. 1427-1436, Dec. 2011.  Official location  
• Chao, Y., He, L., Kenji Suzuki. A new connected-component labeling algorithm, American Journal of Engineering and Technology Research, Vol. 11, pp. 1099-1104, Dec. 2011.
• Kenji Suzuki, Epstein M.L., Kohlbrenner R., Garg S., Hori M., Oto A., Baron R.L.. Quantitative radiology: Automated CT liver volumetry compared with interactive volumetry and manual volumetry, American Journal of Roentgenology, Vol. 197, No. 4, pp. W706-W712, Oct. 2011.  Official location  
• Liao S., Penney B.C., Wroblewski K., Zhang H., Simon C.A., Kampalath R., Shih M.-C., Shimada N., Chen S., Salgia R., Appelbaum D.E., Kenji Suzuki, Chen C.-T., Pu Y.. Prognostic value of metabolic tumor burden on ¹⁸F-FDG PET in nonsurgical patients with non-small cell lung cancer, European Journal of Nuclear Medicine and Molecular Imaging, Vol. 39, pp. 27-38, Sept. 2011.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Nakamura, T.. A new first-scan strategy for raster-scan-based labeling algorithms, Journal of Information Processing Society of Japan, Vol. 52, pp. 1813-1819, Apr. 2011.
• Chen, S., Kenji Suzuki, MacMahon, H.. Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification, Medical Physics, Vol. 38, No. 4, pp. 1844-1858, Mar. 2011.  Official location  
• Jian-Wu Xu, Kenji Suzuki. Massive-training support vector regression and Gaussian process for false-positive reduction in computer-aided detection of polyps in CT colonography, Medical Physics, Vol. 38, No. 4, pp. 1888-1902, Mar. 2011.  Official location  
• He L., Chao Y., Kenji Suzuki. Two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images, IEEE Transactions on Image Processing, Vol. 20, No. 8, pp. 2122-2134, Feb. 2011.  Official location  
• Yu, Q., He, L., Nakamura, T., Kenji Suzuki, Chao, Y.. A Multilayered Partitioning Image Registration Method for Chest-Radiograph Temporal Subtraction, American Journal of Engineering and Technology Research, Vol. 11, pp. 2422-2427, 2011.
• He, L., Chao, Y., Kenji Suzuki, Yu, Q., Tang, W., Shi, Z.. An Algorithm for Labeling Connected Components and Holes, American Journal of Engineering and Technology Research, Vol. 11, pp. 2149-2154, 2011.
• Lostumbo, A., Kenji Suzuki, Dachman, A.H.. Flat lesions in CT colonography, Abdominal Imaging, Vol. 35, No. 5, pp. 578-583, Oct. 2010.  Official location  
• Shi, Z., Bai, J., Kenji Suzuki, He, L., Yao, Q., Nakamura, T.. A method for enhancing dot-like regions in chest X-rays based on directional scale LoG filter, Journal of Information and Computational Science, Vol. 7, No. 8, pp. 1689-1696, Aug. 2010.  Official location  
• He, L., Chao, Y., Kenji Suzuki. A Run-based one-and-a-half-scan connected-component labeling algorithm, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24, No. 4, pp. 557-579, June 2010.  Official location  
• Kenji Suzuki, Zhang, J., Xu, J.. Massive-training artificial neural network coupled with laplacian-eigenfunction-based dimensionality reduction for computer-aided detection of polyps in CT colonography, IEEE Transactions on Medical Imaging, Vol. 29, No. 11, pp. 1907-1917, June 2010.  Official location  
• Kenji Suzuki, Kohlbrenner, R., Epstein, M.L., Obajuluwa, A.M., Xu, J., Hori, M.. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms, Medical Physics, Vol. 37, No. 5, pp. 2159-2166, Apr. 2010.  Official location  
• He, L., Chao, Y., Kenji Suzuki. An efficient first-scan method for label-equivalence-based labeling algorithms, Pattern Recognition Letters, Vol. 31, No. 1, pp. 28-35, Jan. 2010.  Official location  
• Lostumbo, A., Wanamaker, C., Tsai, J., Kenji Suzuki, Dachman, A.H.. Comparison of 2D and 3D Views for Evaluation of Flat Lesions in CT Colonography, Academic Radiology, Vol. 17, No. 1, pp. 39-47, Jan. 2010.  Official location  
• Kenji Suzuki, Rockey, D.C., Dachman, A.H.. CT colonography: Advanced computer-aided detection scheme utilizing MTANNs for detection of "missed" polyps in a multicenter clinical trial, Medical Physics, Vol. 37, No. 1, pp. 12-21, Dec. 2009.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Nakamura, T., Itoh, H.. A high-speed labeling algorithm for three-dimensional binary images, Transactions of IEICE, Vol. J92-D, No. 12, pp. 2261-2269, Dec. 2009.
• Oda, S., Awai, K., Kenji Suzuki, Yanaga, Y., Funama, Y., MacMahon, H., Yamashita, Y.. Performance of radiologists in detection of small pulmonary nodules on chest radiographs: Effect of rib suppression with a massive-training artificial neural network, American Journal of Roentgenology, Vol. 193, No. 5, pp. W397-W402, Nov. 2009.  Official location  
• Hori, M., Oto, A., Orrin, S., Kenji Suzuki, Baron, R.L.. Diffusion-weighted MRI: A new tool for the diagnosis of fistula in ano, Journal of Magnetic Resonance Imaging, Vol. 30, No. 5, pp. 1021-1026, Oct. 2009.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Wu, K.. Fast connected-component labeling, Pattern Recognition, Vol. 42, No. 9, pp. 1977-1987, Sept. 2009.  Official location  
• Kenji Suzuki. A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD), Physics in Medicine and Biology, Vol. 54, No. 18, pp. S31-S45, Aug. 2009.  Official location  
• Wu, K., Otoo, E., Kenji Suzuki. Optimizing two-pass connected-component labeling algorithms, Pattern Analysis and Applications, Vol. 12, No. 2, pp. 117-135, June 2009.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Nakamura, T., Itoh, H.. A strategy for efficiency improvement of the first-scan in raster-scan-based labeling algorithms, Transactions of IEICE, vol. J92-D, no. 6, pp. 951-955, June 2009.
• Takeshi Inaba, Lifeng He, Kenji Suzuki, Kazuhito Murakami, Yuyan Chao. A Genetic-Algorithm-Based Temporal Subtraction for Chest Radiographs, Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 13, no. 3, pp. 289-296, May 2009.  Official location  
• Shi Z., He L., Nakamura T., Kenji Suzuki, Itoh H.. Survey on Neural Networks Used for Medical Image Processing, International Journal of Computational Science, Vol. 3, pp. 86-100, Feb. 2009.
• He, L., Chao, Y., Kenji Suzuki, Nakamura, T., Itoh, H.. A label-equivalence-based one-scan labeling algorithm, Journal of Information Processing Society of Japan, Vol. 50, pp. 1660-1667, 2009.
• Lifeng, H., Yuyan, C., Kenji Suzuki, Nakamura, T., Itoh, H.. A high-speed run-based two-scan labeling algorithm, Journal of the Institute of Image Information and Television Engineers, Vol. 62, No. 9, pp. 1461-1465, July 2008.  Official location  
• Kenji Suzuki, Yoshida, H., Näppi, J., Armato III, S.G., Dachman, A.H.. Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography, Medical Physics, Vol. 35, No. 2, pp. 694-703, Feb. 2008.  Official location  
• Shi, Z., Chao, Y., He, L., Kenji Suzuki, Nakamura, T., Itoh, H.. Object Location and Track in Image Sequences by Means of Newral Networks, International Journal of Computational Science, Vol. 2, No. 2, pp. 274-285, 2008.
• He, L., Chao, Y., Kenji Suzuki, Nakamura, T., Itoh, H.. An efficient two-scan connected-component labeling algorithm, Transactions of IEICE, Vol. J91-D, pp. 1016-1024, 2008.
• He, L., Chao, Y., Kenji Suzuki. A run-based two-scan labeling algorithm, IEEE Transactions on Image Processing, Vol. 17, No. 5, pp. 749-756, 2008.  Official location  
• King M., Giger M.L., Suzuki K., Pan X.. Feature-based characterization of motion-contaminated calcified plaques in cardiac multidetector CT, Medical Physics, vol. 34, no. 12, pp. 4860-4875, Dec. 2007.
• King, M., Giger, M.L., Kenji Suzuki, Bardo, D.M.E., Greenberg, B., Lan, L., Pan, X.. Computerized assessment of motion-contaminated calcified plaques in cardiac multidetector CT, Medical Physics, Vol. 34, No. 12, pp. 4876-4889, Nov. 2007.  Official location  
• Yuan, Y., Giger, M.L., Li, H., Kenji Suzuki, Sennett, C.. A dual-stage method for lesion segmentation on digital mammograms, Medical Physics, Vol. 34, No. 11, pp. 4180-4193, Oct. 2007.  Official location  
• Doshi, T., Rusinak, D., Halvorsen, R.A., Rockey, D.C., Kenji Suzuki, Dachman, A.H.. CT colonography: False-negative interpretations, Radiology, Vol. 244, No. 1, pp. 165-173, July 2007.  Official location  
• Yu-Yan Chao, Li-Feng He, Tsuyoshi Nakamura, Zheng-Hao Shi, Kenji Suzuki, Hidenori Itoh. An improvement of Herbrand's theorem and its application to model generation theorem proving, Journal of Computer Science and Technology, Vol. 22, No. 4, pp. 541-553, July 2007.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Shi, Z., Itoh, H.. An Improvement on Sub-Herbrand Universe Computation, The Open Artificial Intelligence Journal, Vol. 1, pp. 12-18, 2007.
• Kenji Suzuki, Yoshida, H., Näppi, J., Dachman, A.H.. Massive-training artificial neural network (MTANN) for reduction of false positives in computer-aided detection of polyps: Suppression of rectal tubes, Medical Physics, Vol. 33, No. 10, pp. 3814-3824, Sept. 2006.  Official location  
• Muramatsu, C., Li, Q., Schmidt, R., Kenji Suzuki, Shiraishi, J., Newstead, G., Doi, K.. Experimental determination of subjective similarity for pairs of clustered microcalcifications on mammograms: Observer study results, Medical Physics, Vol. 33, No. 9, pp. 3460-3468, Aug. 2006.  Official location  
• Shiraishi, J., Li, Q., Kenji Suzuki, Engelmann, R., Doi, K.. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: Localized search method based on anatomical classification, Medical Physics, Vol. 33, No. 7, pp. 2642-2653, June 2006.  Official location  
• Kenji Suzuki, Abe, H., MacMahon, H., Doi, K.. Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN), IEEE Transactions on Medical Imaging, Vol. 25, No. 4, pp. 406-416, Apr. 2006.  Official location  
• Li, F., Arimura, H., Kenji Suzuki, Shiraishi, J., Li, Q., Abe, H., Engelmann, R., Sone, S., MacMahon, H., Doi, K.. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization, Radiology, Vol. 237, No. 2, pp. 684-690, Nov. 2005.  Official location  
• Li, Q., Li, F., Kenji Suzuki, Shiraishi, J., Abe, H., Engelmann, R., Nie, Y., MacMahon, H., Doi, K.. Computer-aided diagnosis in thoracic CT, Seminars in Ultrasound, CT and MRI, Vol. 26, No. 5, pp. 357-363, Oct. 2005.  Official location  
• Kenji Suzuki, Doi, K.. How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT?, Academic Radiology, Vol. 12, No. 10, pp. 1333-1341, Oct. 2005.  Official location  
• Kenji Suzuki, Li, F., Sone, S., Doi, K.. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network, IEEE Transactions on Medical Imaging, Vol. 24, No. 9, pp. 1138-1150, Aug. 2005.  Official location  
• Muramatsu, C., Li, Q., Kenji Suzuki, Schmidt, R.A., Shiraishi, J., Newstead, G.M., Doi, K.. Investigation of psychophysical measure for evaluation of similar images for mammographic masses: Preliminary results, Medical Physics, Vol. 32, No. 7, pp. 2295-2304, June 2005.  Official location  
• Kenji Suzuki, Shiraishi, J., Abe, H., MacMahon, H., Doi, K.. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network, Academic Radiology, Vol. 12, No. 2, pp. 191-201, Feb. 2005.  Official location  
• Kenji Suzuki. Determining the receptive field of a neural filter, Journal of Neural Engineering, Vol. 1, No. 4, pp. 228-237, Dec. 2004.  Official location  
• Kenji Suzuki. Supervised Nonlinear Image Processing Based on Artificial Neural Networks: Basic Principle of Neural Image Processing and Its Applications, 核医学技術, vol. 24, no. 5, pp. 433-442, Dec. 2004.
• Li F., Aoyama M., Shiraishi J., Abe H., Li Q., Kenji Suzuki, Engelmann R., Sone S., MacMahon H., Doi K.. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy, American Journal of Roentgenology, Vol. 183, No. 5, pp. 1209-1215, Nov. 2004.  Official location  
• Arimura, H., Katsuragawa, S., Kenji Suzuki, Li, F., Shiraishi, J., Sone, S., Doi, K.. Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening, Academic Radiology, Vol. 11, No. 6, pp. 617-629, June 2004.  Official location  
• Kenji Suzuki, Horiba, I., Sugie, N., Nanki, M.. Extraction of Left Ventricular Contours From Left Ventriculograms by Means of a Neural Edge Detector, IEEE Transactions on Medical Imaging, Vol. 23, No. 3, pp. 330-339, Mar. 2004.  Official location  
• Kenji Suzuki, Horiba, I., Sugie, N.. Neural Edge Enhancer for Supervised Edge Enhancement from Noisy Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 12, pp. 1582-1596, Dec. 2003.  Official location  
• Uchiyama Y., Katsuragawa S., Abe H., Shiraishi J., Li F., Li Q., Zhang C.-T., Kenji Suzuki, Doi K.. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography, Medical Physics, Vol. 30, No. 9, pp. 2440-2454, Aug. 2003.  Official location  
• Kenji Suzuki, Armato III, S.G., Li, F., Sone, S., Doi, K.. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography, Medical Physics, Vol. 30, No. 7, pp. 1602-1617, July 2003.  Official location  
• Kenji Suzuki, 堀場勇夫, 杉江昇. ニューラルエッジ検出器によるノイズに埋もれた画像からのエッジ検出, 電子情報通信学会論文誌 D-2, vol. J86-D-2, no. 4, pp. 579-583, Apr. 2003.
• Kenji Suzuki, Horiba, I., Sugie, N., Nanki, M.. Contour extraction of left ventricular cavity from digital subtraction angiograms using a neural edge detector, Systems and Computers in Japan, Vol. 34, No. 2, pp. 55-69, Jan. 2003.  Official location  
• Kenji Suzuki, Horiba, I., Sugie, N.. Linear-time connected-component labeling based on sequential local operations, Computer Vision and Image Understanding, Vol. 89, No. 1, pp. 1-23, Jan. 2003.  Official location  
• Kenji Suzuki, Horiba, I., Sugie, N., Nanki, M.. Neural filter with selection of input features and its application to image quality improvement of medical image sequences, IEICE Transactions on Information and Systems, Vol. E85-D, No. 10, pp. 1710-1718, Oct. 2002.  Official location  
• Kenji Suzuki, Horiba, I., Sugie, N.. Efficient approximation of neural filters for removing quantum noise from images, IEEE Transactions on Signal Processing, Vol. 50, No. 7, pp. 1787-1799, July 2002.  Official location  
• Ninagawa K., Umeyama T., Kenji Suzuki, Sugie N.. Sound Source Separation in the Frequency Domain with Image Processing, IEEJ Transactions on Electronics, Information and Systems, Vol. 121, No. 12, pp. 1866-1874, Dec. 2001.
• Kenji Suzuki, 堀場勇夫, 杉江昇, 南木道生. Improving Image Quality of Medical X-ray Image Sequences Using a Neural Filter with Selection of Input Features, 情報処理学会論文誌, vol. 42, no. 8, pp. 2176-2188, Aug. 2001.
• Kenji Suzuki, Horiba, I., Sugie, N.. A simple neural network pruning algorithm with application to filter synthesis, Neural Processing Letters, Vol. 13, No. 1, pp. 43-53, Feb. 2001.  Official location  
• Kenji Suzuki, 堀場勇夫, 杉江昇. Fast Connected-Component Labeling through Sequential Local Operations in the Course of Forward Raster Scan Followed by Backward Raster Scan, 情報処理学会論文誌, vol. 41, no. 11, pp. 3070-3081, Nov. 2000.
• Kenji Suzuki, 堀場勇夫, 杉江昇, 南木道生. ニューラルエッジ検出器を利用したDSAにおける左心室の輪郭抽出, 電子情報通信学会論文誌 D, vol. J83-D2, no. 10, pp. 2017-2029, Oct. 2000.
• Kenji Suzuki, 堀場勇夫, 杉江昇. An Analysis of the Neural Filter Trained to Improve Quality of images with Quantum Noise and Realization of Approximate Filter, 情報処理学会, vol. 41, no. 3, pp. 711-721, Mar. 2000.
• Kenji Suzuki, 林達也, 池田重之, 堀場勇夫, 杉江昇, 南木道生. ニューラルフィルタを用いた医用低線量X線動画像の画質改善, 電気学会論文誌 C, vol. 199, no. 11, pp. 1383-1391, Nov. 1999.
• Kenji Suzuki, 堀場勇夫, 杉江昇. A Method for Determining Reduced Structure of Neural Filter, 情報処理学会論文誌, vol. 40, no. 12, pp. 4226-4238, Dec. 1996.
• 上田浩次, 山田宗男, 堀場勇夫, 池谷和夫, Kenji Suzuki. アナログ出力ニューラルネットワークを用いた駐車率の直接推定方法, 情報処理学会論文誌, vol. 36, no. 3, pp. 627-635, Mar. 1995.
• Kenji Suzuki, Horiba I., Ikegaya K., Nanki M.. Recognition of Coronary Arterial Stenosis Using Neural Network on DSA System, Systems and Computers in Japan, Vol. 26, No. 8, pp. 66-74, 1995.  Official location  
• Kenji Suzuki, 堀場勇夫, 池谷和夫, 南木道生. ニューラルネットを用いた冠動脈DSAにおける狭窄率認識, 電子情報通信学会論文誌 D-2, vol. 77, no. 9, pp. 1910-1916, Sept. 1994.

Book

• Rahmaniar W, Deng Z., Yang Y., Jin Z., Suzuki K.. Decentralized Diagnostics: The Role of Federated Learning in Modern Medical Imaging, Advances in Intelligent Disease Diagnosis and Treatment, Springer, pp. 223-239, Sept. 2024.
• Ze Jin, Taiguang Yuan, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Kenji Suzuki. Radiomics: Approach to Precision Medicine, Artificial Intelligence and Machine Learning for Healthcare, Springer, pp. 17-29, Sept. 2022.  Official location  
• Jon Krohn, Kenji Suzuki, 清水美樹. Python, TensorFlowで実践する深層学習入門 しくみの理解と応用, Python, TensorFlowで実践する深層学習入門 しくみの理解と応用, 東京化学同人, pp. 304, Sept. 2022.
• Kenji Suzuki. Computerized Detection of Lesions in Diagnostic Images with Early Deep Learning Models, Machine and Deep Learning in Oncology, Medical Physics and Radiology, Springer, Cham, pp. 175-204, Feb. 2022.
• Kenji Suzuki. 医用画像処理における深層学習, 先進医療NAVIGATOR 医療とAI最前線, 日本医学出版, pp. 8-10, Feb. 2022.
• Kenji Suzuki. Deep Learning in Medical Image Processing and Computer-Aided Diagnosis, Biomedical Engineering, Jenny Stanford Publishing, pp. 297-318, Nov. 2021.
• Kenji Suzuki. 大規模学習ニューラルネット（MTANN）, 医療AIとディープラーニングシリーズ 2020-2021年版 はじめての医用画像ディープラーニング －基礎・応用・事例－, オーム社, pp. 67-69, Mar. 2020.
• Zarshenas A., Suzuki K.. Deep Learning for Medical Image Processing: Bones and Soft Tissue Separation in Chest Radiographs, Lung Cancer and Imaging, IOP Publishing, Dec. 2019.  Official location  
• Greenspan H., Tanno R., Erdt M., Arbel T., Baumgartner C., Dalca A., Sudre C.H., Wells III W.M., Drechsler K., Linguraru M.G., Oyarzun Laura C., Shekhar R., Wesarg S., González Ballester M.Á., Suzuki K., Liao H., Wang Q., van Ginneken B., Zhou L.. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures, Lecture Notes in Computer Science, Springer, Vol. 11840, Oct. 2019.  Official location  
• Suzuki K., Reyes M., Syeda-Mahmood T., Konukoglu E., Glocker B., Wiest R., Gur Y., Greenspan H., Madabhushi A.. Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, Lecture Notes in Computer Science, Springer, Vol. 11797, Oct. 2019.  Official location  
• Liao H., Balocco S., Wang G., Zhang F., Liu Y., Ding Z., Duong L., Phellan R., Zahnd G., Breininger K., Albarqouni S., Moriconi S., Lee S.-L., Demirci S., Suzuki K., Greenspan H., Wang Q., van Ginneken B., Zhou L.. Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting, Lecture Notes in Computer Science, Springer, Vol. 11794, Oct. 2019.  Official location  
• Kenji Suzuki, Chen Yisong. Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging, Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging, Springer Cham, Jan. 2018.  Official location  
• Zarshenas, A., Kenji Suzuki. Introduction to binary coordinate ascent: New insights into efficient feature subset selection for machine learning, Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging, Springer, pp. 59-83, Jan. 2018.  Official location  
• Tajbakhsh, N., Kenji Suzuki. A comparative study of modern machine learning approaches for focal lesion detection and classification in medical images: BoVW, CNN and MTANN, Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging, Springer, Vol. 140, pp. 31-58, Jan. 2018.  Official location  
• Jianwu Xu, Amin Zarshenas, Yisong Chen, Kenji Suzuki. Massive-Training Support Vector Regression With Feature Selection in Application of Computer-Aided Detection of Polyps in CT Colonography, Emerging Developments and Practices in Oncology, IGI Global, 2018.  Official location  
• Kenji Suzuki, Liu J., Zarshenas A., Higaki T., Fukumoto W., Awai, K.. Neural network convolution (NNC) for converting ultra-low-dose to “virtual” high-dose CT images, Lecture Notes in Computer Science (Lecture Notes in Computer Science), Vol. 10541, pp. 334-343, Sept. 2017.  Official location  
• Kenji Suzuki. Computer-aided detection of lung cancer, Image-Based Computer-Assisted Radiation Therapy, Springer, pp. 9-40, Jan. 2017.  Official location  
• Wang Qian, Shi Yinghuan, Suk Heung-Il, Kenji Suzuki. Machine Learning in Medical Imaging (Lecture Notes in Computer Science 10541), Lecture Notes in Computer Science, Springer Cham, vol. 10541, pp. 391, 2017.
• Kenji Suzuki. Computerized Detection of Lesions in Diagnostic Images, Machine Learning in Radiation Oncology: Theory and Applications, Springer International Publishing, pp. 101-131, June 2015.  Official location  
• Chen, S., Kenji Suzuki. Bone suppression in chest radiographs by means of anatomically specific multiple massive-training ANNs combined with total variation minimization smoothing and consistency processing, Computational Intelligence in Biomedical Imaging, Springer, pp. 211-235, July 2014.  Official location  
• Kenji Suzuki. Computational intelligence in biomedical imaging, Computational Intelligence in Biomedical Imaging, pp. 1-406, 2014.  Official location  
• Kenji Suzuki. Pixel-based machine learning in computer-aided diagnosis of lung and colon Cancer, Machine Learning in Healthcare Informatics, Springer, pp. 81-112, Dec. 2013.  Official location  
• Huynh, H.T., Karademir, I., Oto, A., Kenji Suzuki. Liver volumetry in MRI by using fast marching algorithm coupled with 3d geodesic active contour segmentation, Computational Intelligence in Biomedical Imaging, Springer, pp. 141-157, Oct. 2013.  Official location  
• Kenji Suzuki. Artificial Neural Networks - Architectures and Applications, Artificial Neural Networks - Architectures and Applications, Intech, Jan. 2013.  Official location  
• Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang. Machine Learning in Medical Imaging (Lecture Notes in Computer Science 8184), Lecture Notes in Computer Science, Springer Cham, Vol. 8184, pp. 262, 2013.  Official location  
• Kenji Suzuki. Neural Networks, 実践医用画像解析ハンドブック, オーム社, pp. 253-259, Nov. 2012.
• Kenji Suzuki. MTANNs を応用した病巣陰影の識別, 実践医用画像解析ハンドブック, オーム社, pp. 563-567, Nov. 2012.
• Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki. Machine Learning in Medical Imaging (Lecture Notes in Computer Science 7588), Lecture Notes in Computer Science, Springer Berlin, Heidelberg, Vol. 7588, pp. 276, 2012.  Official location  
• Kenji Suzuki. Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, IGI Global, 2012.  Official location  
• Jian-Wu Xu, Kenji Suzuki. Computer-Aided Detection of Polyps in CT Colonography by Means of Feature Selection and Massive-Training Support Vector Regression, Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, IGI Global, 2012.  Official location  
• Sheng Chen, Kenji Suzuki. Computerized Detection of Lung Nodules on Chest Radiographs: Application of Bone Suppression Imaging by Means of Multiple Massive-Training ANNs, Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, IGI Global, pp. 122-144, 2012.  Official location  
• Kenji Suzuki. Computer-aided detection of lung nodules in chest radiographs and thoracic CT, Lung Imaging and Computer Aided Diagnosis, CRC press, pp. 297-318, Aug. 2011.  Official location  
• Kenji Suzuki. Artificial Neural Networks - Industrial and Control Engineering Applications, Artificial Neural Networks - Industrial and Control Engineering Applications, Intech, Apr. 2011.  Official location  
• Kenji Suzuki. Pixel-Based Artificial Neural Networks in Computer-Aided Diagnosis, Artificial Neural Networks - Methodological Advances and Biomedical Applications, Intech, pp. 71-92, Apr. 2011.  Official location  
• Kenji Suzuki. Artificial Neural Networks - Methodological Advances and Biomedical Applications, Artificial Neural Networks - Methodological Advances and Biomedical Applications, Intech, Apr. 2011.  Official location  
• Kenji Suzuki. Computerized Segmentation of Organs by Means of Geodesic Active-Contour Level-Set Algorithm, Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies, Springer, pp. 103-128, Feb. 2011.  Official location  
• Kenji Suzuki. Massive-training artificial neural networks for supervised enhancement/suppression of lesions/patterns in medical images, Focus on Artificial Neural Networks, Nova Science Publishers, pp. 129-150, 2011.  Official location  
• Suzuki Kenji., Wang F., Shen D., Yan P.. Machine Learning in Medical Imaging (Lecture Notes in Computer Science 7009), Lecture Notes in Computer Science, Springer Berlin, Heidelberg, Vol. 7009, pp. 371, 2011.
• Kenji Suzuki, Dachman A. H.. Usefulness of computer-aided diagnosis in CT colonography, Colonoscopia virtual, Liberia Akadia Editorial, pp. 73-88, 2011.
• Kenji Suzuki, Dachman Abraham H.. Computer-Aided Diagnosis in Computed Tomographic Colonography, Atlas of Virtual Colonoscopy, Springer, Oct. 2010.  Official location  
• Kenji Suzuki. Massive-Training Artificial Neural Networks (MTANN) in Computer-Aided Detection of Colorectal Polyps and Lung Nodules in CT, Machine Learning, Intech, pp. 343-366, Feb. 2010.  Official location  
• Mark L. Epstein, Ivan Sheu, Kenji Suzuki. Hessian Matrix-Based Shape Extraction and Volume Growing for 3D Polyp Segmentation in CT Colonography, Pattern Recognition Recent Advances, Intech, pp. 405-418, Feb. 2010.  Official location  
• Fei Wang, Pingkun Yan, Kenji Suzuki, Dinggang Shen. Machine Learning in Medical Imaging (Lecture Notes in Computer Science 6357), Lecture Notes in Computer Science, Springer Berlin, Heidelberg, Vol. 6357, pp. 192, 2010.  Official location  
• Giger, M.L., Kenji Suzuki. Computer-aided diagnosis, Biomedical Information Technology, Academic Press, pp. 359-374, 2008.  Official location  
• Kenji Suzuki. 平滑化 ，エッジ保存平滑化，ぼけ復元，焦点，動き，画像復元, 認知科学辞典, 共立出版, July 2002.

International Conference (Reviewed)

• Zhang C., Jin Z., Hori M., Sofue K., Murakami T., Suzuki K.. AI-aided diagnostic system providing explanations in LI-RADS language in liver cancer diagnosis using MRI, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Yuan T., Jin Z., Tokuda Y., Tomiyama N., Naoi Y., Suzuki K.. Forecast of genetic assessments for tumor response to chemotherapy only with pretherapeutic breast MRI by means of radiogenomic imaging biomarker scheme, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Deng Z., Jin Z., Suzuki K.. Dual-domain MTANN for virtual high-dose imaging in digital breast tomosynthesis (DBT), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Qu T., Yang Y., Jin Z., Suzuki K.. Annotation-free AI learning of lung nodule segmentation in CT using weakly-supervised Massive -training Artificial neural networks, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Kodera S., Mohammad C.S., Jin Z., Watadani T., Abe O., Suzuki K.. Super-efficient AI for lung nodule classification in CT based on small-data massive-training artificial neural network (MTANN), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA 2024), Dec. 2024.
• Yuqiao Yang, Ze Jin, Fumihiko Nakatani, Mototaka Miyake, Kenji Suzuki. “Small-data” Patch-wise Multi-dimensional Output Deep-learning for Rare Cancer Diagnosis in MRI under Limited Sample-size Situation, 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), May 2024.
• Kodera S., Rahmaniar W., Oshibe H., Jin Z., Watadani T., Abe O., Suzuki K.. Super-Efficient Lung Nodule Classification Using Massive-Training Artificial Neural Network (MTANN) Compact Model on LIDC-IDRI Database, 2024 6th International Conference on Image, Video and Signal Processing (IVSP 2024), Mar. 2024.
• Yang Y., Jin Z., Suzuki K.. Federated learning - Game changing AI concept to train AI without sending patient data out from hospitals, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Yang S., Xiang M., Qu T., Jin Z., Suzuki K.. Reconstruction of Fast Acquisition MRI with Under-sampled K-space Data by Using Massive-Training Artificial Neural Networks (MTANNs), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Jin Z., Pang M., Qu T., Oshibe H., Sasage R., Suzuki K.. Feature Map Visualization for Explaining Black-Box Deep Learning Model in Liver Tumor Segmentation, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K.. Development of a small-data deep-learning model based on an MTANN for soft tissue sarcoma diagnosis in MRI, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2023.
• Sirisanwannakul K., Siripool N., Suzuki K., Kongprawechnon W., Karnjana J.. Detection and Correction of Defective Relative Humidity Data Collected from the Greenhouse Environment Using Nested Kalman Filters with Standard Deviation Analysis, 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2023), Oct. 2023.
• Ze Jin, Maolin Pang, Yuqiao Yang, Fahad Parvez Mahdi, Tianyi Qu, Ren Sasage, Kenji Suzuki. Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models, The 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Lecture notes in computer science, LNCS, Oct. 2023.
• Kenji Suzuki. ROC-Score-Based Ensemble Training for Multiple Deep Learning Modules in Classification between Polyps and Non-Polyps in CT Colonography, 2023 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), Oct. 2023.
• Pang M., Jin Z., Qu T., Mahdi F. P., Sasage R., Suzuki K.. Functional Model Visualization for Explaining Massive-Training Artificial Neural Network for Liver Tumor Segmentation, 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC 2023), July 2023.
• Yang S., Xiang M., Qu T., Jin Z., Suzuki K.. Under-sampled Image Reconstruction in Fast Acquisition MRI with Massive-Training Artificial Neural Networks (MTANNs) Deep Learning Approach, 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023), July 2023.
• Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K.. AI-aided Diagnosis of Rare Soft-Tissue Sarcoma by Means of Massive-Training Artificial Neural Network (MTANN), 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023), July 2023.
• Deng Z., Jin Z., Suzuki K.. Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels, 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2023), July 2023.
• Xu L., Mahdi F. P., Jin Z., Noguchi Y., Murata M., Suzuki K.. Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks, SPIE Medical Imaging (SPIE MI), Proceedings of SPIE, Apr. 2023.  Official location  
• Kenji Suzuki. AI-aided Diagnosis and Virtual AI Imaging with Small-Data Deep Learning, The Fifteenth International Conference on eHealth, Telemedicine, and Social Medicine (eTELEMED 2023), Apr. 2023.  Official location  
• Kenji Suzuki. Deep Residual Massive-Training Artificial Neural Network for Image Denoising, 2023 5th International Conference on Image, Video and Signal Processing (IVSP 2023), Mar. 2023.
• Zhipeng Deng, Ze Jin, Kenji Suzuki. Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Multi-scale-Kernel Massive-Training Artificial Neural Network (MTANN) for Generating Virtual High-Dose Images, European Congress of Radiology (ECR 2023), Mar. 2023.
• Zhipeng Deng, Yuqiao Yang, Ze Jin, Kenji Suzuki. FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis, International Conference on Systems, Man, and Cybernetics (IEEE SMC 2022), Oct. 2022.
• Jingyi You, Dongyuan Li, Manabu Okumura, Kenji Suzuki. JPG - Jointly Learn to Align: Automated Disease Prediction and Radiology Report Generation,, The 29th International Conference on Computational Linguistics(COLING 2022), Oct. 2022.
• Yuqiao Yang, Ze Jin, Kenji Suzuki. Federated Tumor Segmentation with Patch-wise Deep Learning Model, 25th International Conference on Medical Image Computing and Computer Assisted InterventionInternational (MICCAI) Workshop on machine learning in medical imaging (MLMI), Sept. 2022.
• Kenji Suzuki. Small data deep learning for lung cancer detection and diagnosis in CT, IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2022),, Proceedings of IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2022), Aug. 2022.
• Yuqiao Yang, Ze Jin, Kenji Suzuki. Federated Learning Coupled with Massive-Training Artificial Neural Networks in Tumor Segmentation in CT Images., The 44th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2022), July 2022.
• Wang L., Qi J., Cheng J., Kenji Suzuki. Action unit detection by exploiting spatial-temporal and label-wise attention with transformer, The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW 2022), Proceedings of 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW 2022), June 2022.
• Kenji Suzuki. Generating simulated higher-dose CT images from ultra-low-dose CT images by means of massive-training artificial neural networks, IUPESM World Congress on Medical Physics and Biomedical Engineering (IUPESM WC2022), June 2022.
• Xiang M., Jin Z., Suzuki K.. Massive-Training Artificial Neural Network (MTANN) for Image Quality Improving in Fast-Acquisition MRI of the Knee, The 6th International Symposium on Biomedical Engineering (ISBE2021), Dec. 2021.
• Sato M., Yang Y., Jin Z., Suzuki K.. Segmentation of Liver Tumor in Hepatic CT by Using MTANN Deep Learning with Small Training Dataset Size, The 6th International Symposium on Biomedical Engineering (ISBE2021), Dec. 2021.
• Onai Y., Mahdi F. P., Jin Z., Suzuki K.. Virtual High-Radiation-Dose Image Generation from Low-Radiation-Dose Image in Digital Breast Tomosynthesis (DBT) Using Massive-Training Artificial Neural Network (MTANN), The 6th International Symposium on Biomedical Engineering (ISBE2021), Dec. 2021.
• Wang L., Wang S., Qi J., Suzuki K.. A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Oct. 2021.
• Xiang M., Jin Z., Suzuki K.. Massive-Training Artificial Neural Network (MTANN) with Special Kernel for Artifact Reduction In Fast-Acquisition MRI of the Knee, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 1210-1213, May 2021.
• Sato M., Jin Z., Suzuki K.. Semantic Segmentation of Liver Tumor in Contrast-enhanced Hepatic CT by Using Deep Learning with Hessian-based Enhancer with Small Training Dataset Size, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), pp. 34-37, May 2021.
• Onai Y., Jin Z., Suzuki K.. Generation of Virtual High-Radiation-Dose Images from Low-Dose Images in Digital Breast Tomosynthesis (DBT) with Massive-Training Artificial Neural Network (MTANN), European Congress of Radiology 2021, Mar. 2021.
• Xiang M., Jin Z., Suzuki K.. Fast Acquisition MRI of the Knee by Means of Massive-Training Artificial Neural Network (MTANN) with Special Kernel, European Congress of Radiology 2021, Mar. 2021.
• Sato M., Jin Z., Suzuki K.. Small-Training-Set Deep Learning for Semantic Segmentation of Liver Tumors in Contrast-enhanced Hepatic CT, European Congress of Radiology 2021, Mar. 2021.
• Taiguang Yuan, Ze Jin, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Takashi Obi, Kenji Suzuki. Prediction of Genetically-Evaluated Tumour Responses to Chemotherapy from Breast MRI using Machine Learning with Model Selection, Journal of Physics: Conference Series, vol. 1780, Oct. 2020.
• Taiguang Yuan, Ze Jin, Tokuda Y., Naoi Y., Tomiyama N., Kenji Suzuki. MR Imaging biomarkers for Prediction of Genetic Assessment for Breast Cancer Recurrence: A Radiogenomics Study, IEICE Technical Committee on Medical Imaging (MI), IEICE Technical Report, pp. 227-230, Jan. 2020.
• Yuchen Wang, Ze Jin, Tokuda Y., Naoi Y., Tomiyama N., Kenji Suzuki. Neural Network Convolution Deep Learning for Semantic Segmentation of Breast Tumor in MRI, The 4th International Symposium on Biomedical Engineering (ISBE2019), Proceeding of 4th International Symposium on Biomedical Engineering (ISBE2019), pp. 286-287, Nov. 2019.
• Taiguang Yuan, Ze Jin, Tokuda Y., Naoi Y., Tomiyama N., Kenji Suzuki. Discovery of MR Imaging Biomarkers for Prediction of Pathological Complete Responses to Chemotherapy for Breast Cancer, The 4th International Symposium on Biomedical Engineering (ISBE2019), Proceeding of 4th International Symposium on Biomedical Engineering (ISBE2019), Nov. 2019.
• Zhao Y., Zarshenas A., Higaki T., Awai K., Suzuki K.. Radiation dose reduction in chest CT at a micro-dose (mD) level by noise simulation and noise-specific anatomic neural network convolution (NNC) deep-learning (DL) with K-means clustering, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2019.
• Zarshenas, A., Liu, J., Forti, P., Kenji Suzuki. Mixture of Deep-Learning Experts for Separation of Bones from Soft Tissue in Chest Radiographs, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, pp. 1321-1326, Oct. 2019.  Official location  
• Taiguang Yuan, Ze Jin, Tokuda, Y., Naoi, Y., Tomiyama, N., Kenji Suzuki. Development of deep-learning segmentation for breast cancer in mr images based on neural network convolution, 2019 8th International Conference on Computing and Pattern Recognition, Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition, pp. 187-191, Oct. 2019.  Official location  
• Zarshenas, A., Kenji Suzuki. Deep Neural Network Convolution for Natural Image Denoising, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, pp. 2534-2539, Oct. 2019.  Official location  
• Martinez-Garcia, M., Zhang, Y., Kenji Suzuki, Zhang, Y.. Measuring system entropy with a deep recurrent neural network model, IEEE International Conference on Industrial Informatics (INDIN), pp. 1253-1256, July 2019.  Official location  
• Kido S., Murakami K., Hashimoto N., Hirano Y., Mabu S., Suzuki K.. Deep Learning Techniques for Automated Segmentation of Diffuse Lung Disease Opacities on CT Images, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Liu J., Zarshenas A., Qadir S., Yang L., Fajardo L. L., Suzuki K.. Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Neural Network Convolution (NNC) Deep Learning, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Zarshenas A., Wang, Y., Liu J., Dai Z., Suzuki K.. Virtual Dual-Energy (VDE) Imaging: Separation of Bones from Soft Tissue in Chest Radiographs (CXRs) by Means of Deep Residual Learning (DRL), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Liu. J, Qadir S., Zarshenas A., Yang L., Fajardo L. L., Suzuki K.. Blinded Observer Study: “Virtual” Full-Dose (VFD) Digital Breast Tomosynthesis (DBT) Images Derived from Reduced-Dose Acquisitions versus Clinical Full-Dose DBT Images, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Zarshenas A., Zhao Y., Liu J., Higaki T., Awai K., Suzuki K.. “Virtual” High-Dose Technology: Radiation Dose Reduction in Thin-Slice Chest CT at a Micro-Dose (mD) Level by Means of 3D Deep Neural Network Convolution (NNC), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Liu J., Zarshenas A., Qadir S., Yang L., Fajardo L. L., Suzuki K.. “Virtual” Full-Dose (VFD) Technology: Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Neural Network Convolution (NNC) Deep Learning, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Liu J., Zarshenas A., Qadir S., Yang L., Fajardo L. L., Suzuki K.. A Two-Stage Deep-Learning Scheme for Reducing Radiation Dose in Digital Breast Tomosynthesis (DBT), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Suzuki K., Zarshenas A., Liu J., Zhao Y., Luo Y.. Historical Overview of Machine Learning (ML) and Deep Learning in Medical Image Analysis - What are the Sources of the Power of Deep Learning?, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Zhao Y., Zarshenas A., Higaki T., Awai K., Suzuki K.. Effect of Simulated Micro-Dose (mD) CT on the Performance of Neural Network Convolution (NNC) Deep-Learning (DL) In Radiation Dose Reduction in Chest CT, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2018.
• Zarshenas A., Zhao Y., Liu J., Higaki T., Fukumoto W., Awai K., Suzuki K. Deep 3D Anatomy-Specific Neural Network Convolution for Radiation Dose Reduction in Chest CT at a Micro-Dose Level, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Proc. International Conference on IEEE Engineering in Medicine & Biology Society (IEEE EMBC), July 2018.
• Liu J., Zarshenas A., Qadir S, Yang L., Fajardo L., Suzuki K.. Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning, The Fourteenth International Workshop on Breast Imaging, Proc.SPIE, Vol. 10718, July 2018.  Official location  
• Liu J., Zarshenas A., Wei Z., Yang L., Fajardo L., Suzuki K.. Sequential Neural Network Convolution (NNC) Deep Learning in Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT): Preliminary Results, 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Proc. International Conference on IEEE Engineering in Medicine & Biology Society (IEEE EMBC), July 2018.
• Liu J., Zarshenas A., Qadir A., Wei Z., Yang L., Fajardo L., Kenji Suzuki. Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing, SPIE Medical Imaging, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 10574, Feb. 2018.  Official location  
• Makkinejad N., Tajbakhsh N., Zarshenas A., Khokhar A., Kenji Suzuki. Reduction in training time of a deep learning model in detection of lesions in CT, SPIE Medical Imaging, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 10574, Feb. 2018.  Official location  
• Hashimoto N., Kenji Suzuki, Liu J., Hirano Y., MacMahon H., Kido S.. Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): Consolidation, ground-glass opacity (GGO), and normal opacity, SPIE Medical Imaging, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 10575, Feb. 2018.  Official location  
• Fukumoto W., Suzuki K., Higaki T., Zhao Y., Zarshenas A., Awai K.. Detection of Solid Pulmonary Nodules in Micro-Dose CT (mDCT) with “Virtual” Higher-Dose (vHD) CT Technology: An Observer Performance Study, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Tajbakhsh N., Zarshenas A., Liu J., Suzuki K.. Investigating the Depth of Convolutional Neural Networks (CNNs) in Computer-aided Detection and Classification of Focal Lesions: Lung Nodules in Thoracic CT and Colorectal Polyps in CT Colonography, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Tajbakhsh N., Zarshenas A., Liu J., Suzuki K.. Two Deep-Learning Models for Lung Nodule Detection and Classification in CT: Convolutional Neural Network (CNN) vs Neural Network Convolution (NNC), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Zarshenas A., Zhao Y., Liu J., Higaki T., Awai K., Suzuki K.. Radiation Dose Reduction in Thin-Slice Chest CT at a Micro-Dose (mD) Level by Means of 3D Deep Neural Network Convolution (NNC), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Ito T., Hirano Y., Suzuki K., Kido S.. First-Reader Computerized System for Distinction between Malignant and Benign Nodules on Thoracic CT Images By Means of End-To-End Deep Learning: Convolutional Neural Network (CNN) and Neural Network Convolution (NNC) Approaches, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Zarshenas A., Patel J. V., Liu J., Forti P., Suzuki K.. Virtual Dual-Energy (VDE) Imaging: Separation of Bones from Soft Tissue in Chest Radiographs (CXRs) by Means of Anatomy-Specific (AS) Orientation-Frequency-Specific (OFS) Deep Neural Network Convolution (NNC), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Zarshenas A., Liu J., Suzuki K.. Highly Efficient Biomarker Selection (BS) Based on Novel Binary Coordinate Accent (BCA) for Machine Learning with a Large Dataset in Radiomics, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Liu J., Zarshenas A., Wei Z., Yang L., Fajardo L. L., Suzuki K.. Computer-Based Interactive Demonstration and Comparative Study: Virtual Full-Dose (VFD) Digital Breast Tomosynthesis (DBT) Images Derived From Reduced-Dose Acquisitions versus Clinical Full-Dose DBT Images, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Suzuki K., Zarshenas A., Liu J., Zhao Y., Luo Y.. What Was Changed in Machine Learning (ML) in Medical Image Analysis After the Introduction of Deep Learning?, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Liu J., Zarshenas A., Wei Z., Yang L., Fajardo L. L., Suzuki K.. Virtual High-Dose (VHD) Technology: Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Supervised Deep-Learning Image Processing (DLIP), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Tajbakhsh N., Zarshenas A., Liu J., Suzuki K.. How Deep Should We Go with Deep Learning in Medical Image Analysis?, Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2017.
• Tajbakhsh N., Liu J., Fukumoto W., Higaki T., Awai K., Suzuki K.. Conversion of ultra-low-dose (ULD) to “virtual” high-dose (VHD) thin-slice chest CT by means of 3D supervised volume-based artificial neural network (ANN), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2016.
• Liu J., Zarshenas A., Fajardo L., Suzuki K.. Radiation dose reduction in digital breast tomosynthesis (DBT) by means of patch-based trainable nonlinear regression (PTNR), Scientific Assembly and Annual Meeting of Radiological Society of North America (RSNA), Nov. 2016.
• Suzuki Kenji, Zarshenas M., Liu J., Fan Y., Makkinejad N., Forti P., Dachman A.. Development of Computer-Aided Diagnostic (CADx) System for Distinguishing Neoplastic from Nonneoplastic Lesions in CT Colonography (CTC): Toward CTC beyond Detection, IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2015), Proc. IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2015), pp. 2262-2266, Oct. 2015.
• Kenji Suzuki. Patch-based Machine Learning and Deep Learning in Medical Image Processing and Diagnosis, 4th International Conference on Informatics, Electronics & Vision (ICIEV 2015), Proc. 4th International Conference on Informatics, Electronics & Vision (ICIEV 2015), pp. 42-43, June 2015.
• Kenji Suzuki. Mining of Training Samples for Multiple Learning Machines in Computer-Aided Detection of Lesions in CT Images, IEEE ICDM Workshop on Data Mining in Medical Imaging (DMMI), 2014 IEEE International Conference on Data Mining Workshop, pp. 982-989, Dec. 2014.
• Cao, G., Liu, Y., Kenji Suzuki. A new method for false-positive reduction in detection of lung nodules in CT images, 2014 19th International Conference on Digital Signal Processing, International Conference on Digital Signal Processing, DSP, Vol. 2014, pp. 474-479, Aug. 2014.  Official location  
• Tanaka R., Sanada S., Oda M., Mitsutaka, M., Kenji Suzuki, Sakuta K., Kawashima H.. Quantitative analysis of rib movement based on dynamic chest bone images: Preliminary results, PIE Medical Imaging, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 9034, Feb. 2014.  Official location  
• Kenji Suzuki, Huynh, H.T., Liu, Y., Calabrese, D., Zhou, K., Oto, A., Hori, M.. Computerized segmentation of liver in hepatic CT and MRI by means of level-set geodesic active contouring, IEEE Engineering in Medicine and Biology Conference (IEEE EMBC), Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 2984-2987, July 2013.  Official location  
• Kenji Suzuki, Hori, M., Iinuma, G., Dachman, A.H.. Effect of CADe on radiologists' performance in detection of "difficult" polyps in CT colonography, SPIE Medical Imaging (SPIE MI), Proceedings of SPIE - The International Society for Optical Engineering, Vol. 8670, Feb. 2013.  Official location  
• He L., Chao Y., Yang Y., Li S., Kenji Suzuki. A Novel Two-Scan Connected-Component Labeling Algorithm, Special Volume of the World Congress on Engineering 2012, IAENG Transactions on Engineering Technologies: Special Volume of the World Congress on Engineering 2012, pp. 445-459, Jan. 2013.  Official location  
• He, L., Chao, Y., Kenji Suzuki. A new algorithm for labeling connected-components and calculating the Euler number, connected-component number, and hole number, International Conference on Pattern Recognition, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp. 3099-3102, Nov. 2012.  Official location  
• Chen, S., Kenji Suzuki. Bone suppression in chest radiographs by means of anatomically specific multiple massive-training ANNs, International Conference on Pattern Recognition, Proceedings - International Conference on Pattern Recognition, pp. 17-20, Nov. 2012.  Official location  
• Yu, Q., He, L., Nakamura, T., Kenji Suzuki, Chao, Y.. A multilayered partitioning image registration method for chest-radiograph temporal subtraction, 2012 International Conference on Computer Science and Information Processing (CSIP 2012), Proceedings - 2012 International Conference on Computer Science and Information Processing, CSIP 2012, pp. 181-184, Aug. 2012.  Official location  
• He, L., Chao, Y., Kenji Suzuki. A new two-scan algorithm for labeling connected components in binary images, World Congress on Engineering, Lecture Notes in Engineering and Computer Science, Vol. 2198, pp. 1141-1146, July 2012.  Official location  
• Yu, Q., He, L., Chao, Y., Kenji Suzuki, Nakamura, T.. A mutual-information-based image registration method for chest-radiograph temporal subtraction, 2012 International Conference on Computer Science and Information Processing (CSIP 2012), Proceedings - 2012 International Conference on Computer Science and Information Processing, CSIP 2012, pp. 1098-1101, July 2012.  Official location  
• Jian-Wu Xu, Kenji Suzuki. Maximal partial AUC feature selection in computer-aided detection of hepatocellular carcinoma in contrast-enhanced hepatic CT, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 8315, Feb. 2012.  Official location  
• Jian-Wu Xu, Kenji Suzuki. Computer-aided detection of polyps in CT colonography by means of AdaBoost, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 8315, Feb. 2012.  Official location  
• Chao Y., He L., Kenji Suzuki. A new connected-component labeling algorithm, 2011 International Conference on Opto-Electronics Engineering and Information Science (ICOEIS2011), proceeding of 2011 International Conference on Opto-Electronics Engineering and Information Science (ICOEIS2011), Dec. 2011.
• He L., Chao Y., Kenji Suzuki. A Labeling Algorithm for Connected Components and Holes, 2011 International Conference on Opto-Electronics Engineering and Information Science (ICOEIS2011), Proceeding of 2011 International Conference on Opto-Electronics Engineering and Information Science (ICOEIS2011), Dec. 2011.
• Jian-Wu Xu, Kenji Suzuki. Computer-Aided Detection of Polyps in CT Colonography with Pixel-Based Machine Learning Techniques, Machine Learning in Medical Imaging, pp. 360-367, Sept. 2011.
• Xu J., Kenji Suzuki. False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography: A Massive-Training Support Vector Regression Approach, Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities, pp. 47-52, Sept. 2011.
• Kenji Suzuki. Computer-aided diagnosis - research, development, commercialization and clinical implementation, Proceedings of Workshop on Fusion of Information Technology and Medicine, Aug. 2011.
• Jian-Wu Xu, Kenji Suzuki. Computer-aided detection of hepatocellular carcinoma in hepatic CT: False positive reduction with feature selection, Proceedings - 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1097-1100, Mar. 2011.  Official location  
• Ferraro, F.O., Kawaler, E., Kenji Suzuki. A spinning tangent based CAD system for detection of flat lesions in CT colonography, International Symposium on Biomedical Imaging, Proceedings - International Symposium on Biomedical Imaging, pp. 156-159, Mar. 2011.  Official location  
• Chen, S., Kenji Suzuki, MacMahon, H.. Improved computerized detection of lung nodules in chest radiographs by means of "virtual dual-energy" radiography, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7963, Feb. 2011.  Official location  
• Kenji Suzuki, Armato III S.G., Engelmann R., Caligiuri P., MacMahon H.. Temporal subtraction of "virtual dual-energy" chest radiographs for improved conspicuity of growing cancers and other pathologic changes, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7963, Feb. 2011.  Official location  
• Xu, J.-W., Kenji Suzuki, Hori, M., Oto, A., Baron, R.. Computer-aided detection of hepatocellular carcinoma in multiphase contrast-enhanced hepatic CT: A preliminary study, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7963, Feb. 2011.  Official location  
• Kenji Suzuki. Recent Advances in Reduction of False Positives in Computerized Detection of Polyps in CT Colonography, Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities (Lecture Notes in Computer Science), Vol. 6668, pp. 32-39, 2011.
• Kenji Suzuki, Xu J., Zhang J., Sheu I.. Principal-Component Massive-Training Machine-Learning Regression for False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography, International Workshop on Machine Learning in Medical Imaging, Machine Learning in Medical Imaging (Lecture Notes in Computer Science), Springer Berlin Heidelberg, Vol. 6357, pp. 182-189, Sept. 2010.
• He, L., Inaba, T., Kenji Suzuki, Murakami, K., Chao, Y., Tanga, W., Shie, Z., Nakamura, T.. A global registration method for temporal subtraction of chest radiographs, 2010 International Conference on Image Processing and Pattern Recognition in Industrial Engineering, Proceedings of SPIE - The International Society for Optical Engineering, Vol. 7820, Aug. 2010.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Tang, W., Shi, Z., Nakamura, T.. An efficient run-based connected-component labeling algorithm for three-dimensional binary images, 2010 International Conference on Image Processing and Pattern Recognition in Industrial Engineering, Proceedings of SPIE - The International Society for Optical Engineering, Vol. 7820, Aug. 2010.  Official location  
• Shi Z., Kenji Suzuki, He L.. A filtering method for enhancing dot-like regions in chest x-rays, 8th International Bioinformatics Workshop (IBW2010), Proc. the 8th International Bioinformatics Workshop (IBW2010), June 2010.
• Kenji Suzuki, Epstein, M.L., Xu, J., Obara, P., Rockey, D.C., Dachman, A.H.. Automated scheme for measuring polyp volume in CT colonography using Hessian matrix-based shape extraction and 3D volume growing, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7624, Feb. 2010.  Official location  
• Kenji Suzuki, Epstein, M.L., Kohlbrenner, R., Obajuluwa, A., Xu, J., Hori, M., Baron, R.. CT liver volumetry using geodesic active contour segmentation with a level-set algorithm, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7624, Feb. 2010.  Official location  
• Shi Z., Kenji Suzuki, He L.. Reducing FPs in nodule detection using neural networks ensemble, 2nd International Symposium on Information Science and Engineering, ISISE 2009, 2nd International Symposium on Information Science and Engineering, ISISE 2009, pp. 331-333, Dec. 2009.  Official location  
• He, L., Chao, Y., Kenji Suzuki, Itoh, H.. A fast first-scan algorithm for label-equivalence-based connected-component labeling, IEEE International Conference on Image Processing (IEEE ICIP), Proceedings - International Conference on Image Processing, ICIP, pp. 4013-4016, Nov. 2009.  Official location  
• Suzuki Kenji, Hori M, McFarland E. G., Friedman A. C., Iinuma G., Rockey D. C., Dachman, A. H.. Observer performance study with CAD in detection of polyps in false-negative cases: Preliminary results, 10th International Symposium on Virtual Colonoscopy (ISVC), Proc. International Symposium on Virtual Colonoscopy (ISVC), p. 135, Aug. 2009.
• Lifeng He, Yuyan Chao, Kenji Suzuki, Hidenori Itoh. A Run-Based One-Scan Labeling Algorithm, International Conference Image Analysis and Recognition, Image Analysis and Recognition, Springer Berlin Heidelberg, pp. 93-102, July 2009.
• Rockey, D.C., Kenji Suzuki, Sheu, I., Dachman, A.H.. A CAD utilizing 3D massive-training ANNs for detection of flat lesions in CT colonography: Preliminary results, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 7260, Feb. 2009.  Official location  
• Kenji Suzuki. Segmentation of lesions with improved specificity in computer-aided diagnosis using a massive-training artificial neural network (MTANN), 7th International Conference on Machine Learning and Applications, ICMLA 2008, Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008, pp. 523-527, Dec. 2008.  Official location  
• Kenji Suzuki, Shi Z., Zhang J.. Supervised enhancement of lung nodules by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD), 2008 19th International Conference on Pattern Recognition (ICPR), Proceedings - International Conference on Pattern Recognition, Dec. 2008.  Official location  
• Kenji Suzuki, Sheu I., Rockey D. C., Dachman A. H.. Detection of flat lesions: Performance of a CAD utilizing 3D massive-training ANNs on a cohort from a large multicenter clinical trial, International Symposium on Virtual Colonoscopy (ISVC), Proc. International Symposium on Virtual Colonoscopy (ISVC), pp. 152-153, Oct. 2008.
• Kenji Suzuki, Epstein M. L., Kuo J., Obara P. R., Rockey D. C., Dachman A. H.. CT colonography polyp volumetrics: Fully automated scheme for measuring polyp volume using 3D volume-growing and sub-voxel refinement techniques, International Symposium on Virtual Colonoscopy (ISVC), Proc. International Symposium on Virtual Colonoscopy (ISVC), pp. 149-150, Oct. 2008.
• He L., Chao Y., Kenji Suzuki, Nakamura T., Itoh H.. A survey of labeling algorithms, Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS), Proceeding of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS), pp. 1293-1298, Sept. 2008.
• Inaba T., He L., Chao Y., Kenji Suzuki, Murakami K.. A genetic-algorithm-based method for temporal subtraction in chest radiography, Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS), Proceeding of Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems (SCIS & ISIS), pp. 1619-1624, Sept. 2008.
• Kenji Suzuki, Epstein, M., Sheu, I., Kohlbrenner, R., Rockey, D.C., Dachman, A.H.. Massive-training artificial neural networks for CAD for detection of polyps in CT colonography: False-negative cases in a large multicenter clinical trial, IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI, pp. 684-687, May 2008.  Official location  
• Rodgers, Z.B., King, M., Giger, M.L., Vannier, M., Bardo, D.M.E., Lan, L., Kenji Suzuki. Computerized assessment of coronary calcified plaques in CT images of a dynamic cardiac phantom, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6915, Feb. 2008.  Official location  
• Kenji Suzuki, Sheu, I., Epstein, M., Kohlbrenner, R., Lostumbo, A., Rockey, D.C., Dachman, A.H.. An MTANN CAD for detection of polyps in false-negative CT colonography cases in a large multicenter clinical trial: Preliminary results, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6915, Feb. 2008.  Official location  
• He, L., Chao, Y., Kenji Suzuki. A linear-time two-scan labeling algorithm, Proceedings - International Conference on Image Processing, ICIP, Vol. 5, pp. 241-244, Oct. 2007.  Official location  
• King, M., Giger, M., Kenji Suzuki, Pan, X.. Image quality evaluation of motion-contaminated calcified plaques in cardiac CT, IEEE Nuclear Science Symposium Conference, IEEE Nuclear Science Symposium Conference Record, Vol. 4, pp. 2717-2720, Oct. 2007.  Official location  
• Lostumbo A., Tsai J., Kenji Suzuki, Dachman A. H.. Comparison of 2D and 3D views for measurement and conspicuity of flat lesions in CT colonography, International Symposium on Virtual Colonoscopy (ISVC), Proc. International Symposium on Virtual Colonoscopy (ISVC), pp. 120-121, Oct. 2007.
• Kenji Suzuki, Sheu I., Epstein M. L., Verceles J., Rockey D. C., Dachman A. H.. Performance of CAD based on MTANNs for detection of false-negative polyps in a multicenter clinical trial, International Symposium on Virtual Colonoscopy (ISVC), Proc. International Symposium on Virtual Colonoscopy (ISVC), pp. 93-94, Oct. 2007.
• He L., Chao Y., Kenji Suzuki. A Run-Based Two-Scan Labeling Algorithm, Image Analysis and Recognition (ICIAR), Image Analysis and Recognition, Vol. 4633, pp. 131-142, Aug. 2007.
• Muramatsu C., Li Q., Schmidt R.A., Shiraishi J., Kenji Suzuki, Newstead G.M., Doi K.. Determination of subjective similarity for pairs of masses and pairs of clustered microcalcifications on mammograms: Comparison of similarity ranking scores and absolute similarity ratings, Medical Physics, Vol. 34, No. 7, pp. 2890-2895, June 2007.  Official location  
• King, M., Pan, X., Giger, M., Kenji Suzuki. Motion compensated reconstructions of calcified coronary plaques in cardiac CT, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6510, No. PART 1, Feb. 2007.  Official location  
• Muramatsu, C., Li, Q., Schmidt, R.A., Shiraishi, J., Kenji Suzuki, Newstead, G.M., Doi, K.. Determination of subjective and objective similarity for pairs of masses on mammograms for selection of similar images, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6514, No. PART 1, Feb. 2007.  Official location  
• Kenji Suzuki, Lifeng, H., Khankari, S., Liang, G., Verceles, J., Dachman, A.H.. Mixture of expert artificial neural networks with ensemble training for reduction of various sources of false positives in CAD, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6514, No. PART 1, Feb. 2007.  Official location  
• King, M., Giger, M., Kenji Suzuki, Pan, X.. Computer-aided assessment of cardiac computed tomographic images, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6514, No. PART 1, Feb. 2007.  Official location  
• Kenji Suzuki, Li F., Li Q., MacMahon H., Doi K.. Comparison between 2D and 3D massive-training ANNs (MTANNs) in CAD for lung nodule detection on MDCT, International Journal of Computer Assisted Radiology and Surgery, pp. 354-356, June 2006.  Official location  
• Hui Li, Maryellen L. Giger, Yading Yuan, Li Lan, Kenji Suzuki, Andrew Jamieson, Laura Yarusso, Robert M. Nishikawa, Charlene Sennett. Comparison of Computerized Image Analyses for Digitized Screen-Film Mammograms and Full-Field Digital Mammography Images, International Workshop on Digital Mammography, Digital Mammography, Springer Berlin Heidelberg, Vol. 4046, pp. 569-575, June 2006.
• Yuan, Y., Giger, M.L., Kenji Suzuki, Li, H., Jamieson, A.R.. A two-stage method for lesion segmentation on digital mammograms, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 6144 II, Feb. 2006.  Official location  
• Kenji Suzuki, Shiraishi, J., Li, F., Abe, H., MacMahon, H., Doi, K.. Effect of massive training artificial neural networks for rib suppression on reduction of false positives in computerized detection of nodules on chest radiographs, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 5747, No. I, pp. 97-103, Feb. 2005.  Official location  
• Kenji Suzuki, Li, F., Aoyama, M., Shiraishi, J., Abe, H., Li, Q., Engelmann, R., Sone, S., MacMahon, H., Doi, K.. Effect of CAD on radiologists' responses in distinction between malignant and benign pulmonary nodules on high-resolution CT, SPIE Medical Imaging (SPIE MI), Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol. 5749, pp. 502-507, Feb. 2005.  Official location  
• Kenji Suzuki, Doi K.. Characteristics of a massive training artificial neural network in the distinction between lung nodules and vessels in CT images, CARS 2004 - Computer Assisted Radiology and Surgery, Proceedings of the 18th International Congress and Exhibition, Vol. 1268, pp. 923-928, June 2004.  Official location  
• Li F., Li Q., Aoyama M., Shiraishi J., Abe H., Kenji Suzuki, Engelmann R., Sone S., MacMahon H., Doi K.. Usefulness of computerized scheme for differentiating benign from malignant lung nodules on high-resolution CT, Computer Assisted Radiology and Surgery (CARS 2004), Proceedings of the 18th International Congress and Exhibition, Vol. 1268, pp. 946-951, June 2004.  Official location  
• Kenji Suzuki, Abe H., Li F., Doi K.. Suppression of the contrast of ribs in chest radiographs by means of massive training artificial neural network, SPIE Medical Imaging (SPIE MI), Proceedings of SPIE - The International Society for Optical Engineering, Vol. 5370 II, pp. 1109-1119, Feb. 2004.  Official location  
• Kenji Suzuki, Armato III, S.G., Li, F., Sone, S., Doi, K.. Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT, SPIE Medical Imaging (SPIE MI), Proceedings of SPIE - The International Society for Optical Engineering, Vol. 5032 III, pp. 1355-1366, Feb. 2003.  Official location  
• Kenji Suzuki, Horiba I., Sugie N.. Simple unit-pruning with gain-changing training, IEEE Int. Workshop on Neural Networks for Signal Processing (NNSP), Neural Networks for Signal Processing - Proceedings of the IEEE Workshop, pp. 153-162, Sept. 2001.  Official location  
• Ninagawa K., Umeyama T., Kenji Suzuki, Sugie N.. Voice separation in the frequency domain using image processing, Int. Conf. Software Engineering, Artificial Intelligence, Networking & Parallel/Distributed Computing (SNPD), pp. 746-753, Aug. 2001.
• Ninagawa K., Umeyama T., Kenji Suzuki, Sugie N.. Sound Source Separation in the Frequency Domain with Image Processing, Human-Computer Interaction (INTERACT) 2001, Human-Computer Interaction INTERACT '01: IFIP TC13 International Conference on Human-Computer Interaction, Tokyo, Japan, July 9-13, 2001, pp. 781-782, July 2001.
• Kenji Suzuki, Horiba I., SugieN.. Neural Edge Detector - A Good Mimic of Conventional One Yet Robuster against Noise, International Work-Conference on Artificial Neural Networks 2001, Bio-Inspired Applications of Connectionism (Lecture Notes in Computer Science), Springer Berlin Heidelberg, Vol. 2085, pp. 303-310, June 2001.
• Kenji Suzuki, Horiba I., Sugie N., Nanki M.. Extraction of the contours of left ventricular cavity according with those traced by medical doctors from left ventriculograms using a neural edge detector, SPIE Medical Imaging (SPIE MI), Proc.SPIE, Vol. 4322, pp. 1284-1295, Feb. 2001.  Official location  
• Kenji Suzuki, Horiba I., Sugie N., Nanki M.. Computer-aided diagnosis system for coronary artery stenosis using a neural network, SPIE Medical Imaging (SPIE MI), Proc.SPIE, Vol. 4322, pp. 1771-1782, Feb. 2001.  Official location  
• Kenji Suzuki, Horiba I., Sugie N.. Edge detection from noisy images using a neural edge detector, 2000 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop, Vol. 2, pp. 487-496, Dec. 2000.
• Kenji Suzuki, Horiba I., Sugie N.. Training under achievement quotient criterion, 2000 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501), Vol. 2, pp. 537-546, Dec. 2000.
• Kenji Suzuki, Horiba I., Sugie N.. Neural filter with selection of input features and its application to image quality improvement of medical image sequences, IEEE Int. Symp. Intelligent Signal Processing and Communication Systems (ISPACS), Proc. IEEE Int. Symp. Intelligent Signal Processing and Communication Systems (ISPACS), pp. 783-788, Nov. 2000.
• Kenji Suzuki, Horiba I., Sugie N.. Signal-preserving training for neural networks for signal processing, IEEE Int. Symp. Intelligent Signal Processing and Communication Systems (ISPACS), Proc. IEEE Int. Symp. Intelligent Signal Processing and Communication Systems (ISPACS), pp. 292-297, Nov. 2000.
• Kenji Suzuki, Horiba I., Sugie N.. Fast connected-component labeling based on sequential local operations in the course of forward raster scan followed by backward raster scan, 15th International Conference on Pattern Recognition (ICPR 2000), Proceedings 15th International Conference on Pattern Recognition (ICPR 2000), Vol. 2, pp. 434-437, Sept. 2000.
• Kenji Suzuki, Horiba I., SugieN.. An Approach to Synthesize Filters with Reduced Structures Using a Neural Network, Proceedings of the Second International Conference, Quantum Information II, WORLD SCIENTIFIC, pp. 205-218, Mar. 2000.  Official location  
• Kenji Suzuki, Horiba I., Sugie N.. Efficient approximation of a neural filter for quantum noise removal in X-ray images, IEEE Int. Workshop on Neural Networks for Signal Processing (NNSP), Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468), pp. 370-379, Aug. 1999.
• Kenji Suzuki, Horiba I., Sugie N., Nanki M.. Noise reduction of medical x-ray image sequences using a neural filter with spatiotemporal inputs, . Int. Symp. Noise Reduction for Imaging and Communication Systems (ISNIC), Proc. Int. Symp. Noise Reduction for Imaging and Communication Systems (ISNIC), pp. 85-90, Nov. 1998.
• Kenji Suzuki, Horiba I., Sugie N.. A recurrent neural filter for reducing noise in medical x-ray image sequences, Int. Conf. Neural Information Processing, Proc. Int. Conf. Neural Information Processing (ICONIP), pp. 157-160, Oct. 1998.
• Kenji Suzuki, Horiba I., Sugie N.. Designing the optimal structure of a neural filter, IEEE Int. Workshop on Neural Networks for Signal Processing (NNSP), Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378), pp. 323-332, Sept. 1998.
• Kenji Suzuki, Horiba I., Sugie N., Ikeda S. Improvement of image quality of x-ray fluoroscopy using spatiotemporal neural filter which learns noise reduction, edge enhancement and motion compensation, Int. Conf. Signal Processing Applications and Technology (ICSPAT), Proc. Int. Conf. Signal Processing Applications and Technology (ICSPAT), pp. 1382-1386, Oct. 1996.

Domestic Conference (Reviewed)

• Kentaro Someya, Shogo Kodera, Hiroko Oshibe, Ze Jin, Kenji Suzuki. CTにおける複数のMTANNを組み合わせた肺結節のセグメンテーション, メディカルイメージング連合フォーラム2024, Mar. 2024.
• 小林正貴, 松岡陽, 上原翔, 田中一, 吉田宗一郎, 横山みなと, 河野友亮, 川野圭三, 酒井康之, 藤原基裕, 川村尚子, 奥野哲男, Kenji Suzuki, Itsuo kumazawa, 藤井靖久. ディープラーニングを用いたKUBにおける上部尿路結石自動診断技術の開発, 日本泌尿器科学会東部総会プログラム・抄録集, Vol. 86, pp. 176, Sept. 2022.

International Conference (Not reviewed / Unknown)

• Kenji Suzuki. Small-data AI and Its Applications to Diagnostic Aid and Virtual AI Imaging, the 4th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023), Sept. 2023.
• Kenji Suzuki. Small-Data Deep Learning for Computer-Aided Diagnosis for Rare Diseases, 55th Advanced Materials Congress, Aug. 2023.
• Kenji Suzuki. AI Doctor for Diagnostic Aid and Medical AI Imaging with Deep Learning, 2022 5th Artificial Intelligence and Cloud Computing Conference (AICCC 2022), Dec. 2022.  Official location  
• Kenji Suzuki. AI Doctor and Medical AI Imaging with Deep Learning, The 6th International Conference on Computing and Applied Informatics 2022 (ICCAI 2022), Nov. 2022.  Official location  
• Kenji Suzuki. Small Data Deep Learning in AI-aided Medical Image Diagnosis, The Twelfth International Conference on Ambient Computing, Applications, Services and Technologies (AMBIENT 2022), Nov. 2022.  Official location  
• Kenji Suzuki. AI-aided Diagnosis and Virtual AI Imaging in Medicine, 2022 3rd International Symposium on Artificial Intelligence for Medicine Sciences（ISAIMS 2022), Oct. 2022.  Official location  
• Kenji Suzuki. AI-aided Diagnostic Systems and Virtual AI Imaging in Medicine, the 26th International Conference on Knowledge Based and Intelligent information and Engineering Systems (KES2022), Sept. 2022.  Official location  
• Kenji Suzuki. AI Doctor and Smart Medical Imaging with Deep Learning, 2022 International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE 2022), Sept. 2022.  Official location  
• Kenji Suzuki. AI Doctor and Smart Medical Imaging with Deep Learning, 6th International Conference on Computational Intelligence in Data Mining (ICCIDM 2021), Dec. 2021.  Official location  
• Kenji Suzuki. Artificial Intelligence for Medical Image Processing and Diagnosis, 4th Artificial Intelligence and Cloud Computing Conference (AICCC 2021), Dec. 2021.  Official location  
• Kenji Suzuki. Intelligent Medical Image Processing and Analysis with Deep Learning, The 6th International Conference on Communication, Image and Signal Processing (CCISP 2021), Nov. 2021.  Official location  
• Kenji Suzuki. Artificial intelligence for medical image diagnosis, KES International Conference on Innovation in Medicine and Healthcare (KES-InMed-21), June 2021.  Official location  
• Kenji Suzuki. Artificial Intelligence for Virtual Medical Imaging for Accurate Diagnosis, Advanced Materials Congress, May 2021.
• Kenji Suzuki. Artificial Intelligence in Computer-aided Diagnosis and Medical Image Processing, The 2021 Artificial Intelligence, Big Data and Algorithms (CAIBDA 2021), May 2021.

Domestic Conference (Not reviewed / Unknown)

• Cunyuan Ji, Kengo Oshima, Takumi Urata, Fumikazu Kimura, Keiko Ishii, Takeshi Uehara, Kenji Suzuki, Saori Takeyama, Masahiro Yamaguchi. Predicting the Ki-67 labeling index of endometrioid cancer from the hematoxylin-and-eosin-stained whole slide image, 第22回日本デジタルパソロジー・AI研究会 定時総会, E2, Aug. 2024.  Official location  
• Takuya Ihara, Tomohiko Waki, Koji Fujita, Chenggeer Li, Ze Jin, Hiroko Oshibe, Kenji Suzuki. スモールデータ深層学習を用いた単純X 線画像での舟状骨骨折検知AI システムの開発, 2023年度生体医歯工学共同研究拠点成果報告会, Mar. 2024.
• Kenji Suzuki. 国プロによる医療AIの先端開発の現況と展望, 第63回日本肺癌学会学術集会, Dec. 2022.  Official location  
• Kenji Suzuki. 米国におけるAI画像診断, 第81回日本医学放射線学会総会, Apr. 2022.  Official location  
• Kenji Suzuki. ディープラーニングによる検診のためのAI支援画像診断と医用画像処理, 第28回日本CT検診学会学術集会, Feb. 2021.  Official location  
• Hiroki Imai, Tomoya Nakamura, Kenji Suzuki, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto. H&E染色組織標本に対するブロックベース深層学習による肝細胞癌識別手法の検討, 第18回デジタルパソロジー研究会, 第18回デジタルパソロジー研究会総会 抄録集, p. 37, Aug. 2019.  Official location  

Other Publication

• Wan Azani Mustafa, Kenji Suzuki. Special Issue: Editorial Board Members’ Collection Series in “Computer-Aided Diagnosis and Prognosis of Diseases", Diagnostics, MDPI, Mar. 2023.  Official location  
• Giacinto Barresi, Sabrina Cipolletta, Andreas Triantafyllidis, Kenji Suzuki. Special issue: Intelligent Systems for One Digital Health, International Journal of Environmental Research and Public Health, MDPI, Feb. 2023.  Official location  
• Kenji Suzuki, José Machado. Special Issue: Feature Papers for AI, AI, MDPI, 2023.  Official location  
• Kenji Suzuki. スモールデータ深層学習による医用画像診断支援, Precision Medicine, 北隆館, vol. 5, No. 1, pp. 90-92, Jan. 2022.
• Kenji Suzuki. Special Issue: Frontiers in Artificial Intelligence, AI, MDPI, Dec. 2020.  Official location  
• Kenji Suzuki. 深層学習による医用画像処理と診断支援, Precision Medicine, 北隆館, vol. 3, No. 5, pp. 87-91, May 2020.
• Kenji Suzuki. AI: A New Open Access Journal for Artificial Intelligence, AI, Mar. 2020.
• Onai Y., Jin Z., Obi T., Suzuki K.. Neural Network Convolution (NNC) Deep Learning for Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT), Proceedings of Annual Meeting of Research Center for Biomedical Engineering 2019, Feb. 2020.
• Kenji Suzuki. 医用画像システム, JMAI Letter, Vol. 2, pp. 53-54, 2020.
• Kenji Suzuki. 人工知能（AI）最新動向 – 画像処理, 月刊インナービジョン2019年2月号, Vol. 34, No. 2, pp. 35-37, Feb. 2019.
• Kenji Suzuki. 大腸CTにおけるAI支援画像診断, 月刊インナービジョン2019年1月号, Vol. 34, No. 1, pp. 47-50, Jan. 2019.
• Luc Bidaut, Kenji Suzuki. Special Issue: Computer-Aided Diagnosis and Characterization of Diseases, Diagnostics, MDPI, Sept. 2018.  Official location  
• Kenji Suzuki. ディープラーニングによる画像処理・認識技術の最前線, 月刊インナービジョン2018年7月号, Vol. 33, No. 7, pp. 30-35, July 2018.
• Kenji Suzuki. 画像診断領域における深層学習の最先端技術とAI支援画像診断, Multislice CT 2018 Book（映像情報メディカル増刊号）, vol. 50, no. 8, pp. 40-50, July 2018.
• Kenji Suzuki. Deep Learning Applications, Research and Development in Medical Imaging: Introduction, Vol. 35, No. 4, pp. 177-179, Sept. 2017.
• El-Baz A., Gimel'farb G., Kenji Suzuki. Machine Learning Applications in Medical Image Analysis, Computational and Mathematical Methods in Medicine, Vol. 2017, Apr. 2017.
• Kenji Suzuki, Zhou L., Wang Q.. Machine learning in medical imaging, Pattern Recognition, Vol. 63, Issue C, pp. 465–467, Mar. 2017.
• Shen D., Wu G., Zhang D., Kenji Suzuki, Wang F., Yan P.. Machine learning in medical imaging, Computerized Medical Imaging and Graphics, Vol. 41, pp. 1-2, Apr. 2015.
• Kenji Suzuki, Yan P., Wang F., Shen D.. Machine Learning in Medical Imaging, International Journal of Biomedical Imaging, Vol. 2012, Mar. 2012.
• Kenji Suzuki, Pingkun Yan, Fei Wang, Dinggang Shen. Special issue: Machine Learning in Medical Imaging, International Journal of Biomedical Imaging, Hindawi, Sept. 2011.  Official location  
• 何 立風, 巣 宇燕, Kenji Suzuki, 中村剛士. 同等ラベル解析に基づく三次元2値画像における高速ラベル付けアルゴリズム, 画像ラボ, 日本工業出版, vol. 21, no. 8, pp. 48-52, Aug. 2010.
• Kenji Suzuki. Special issue: Machine Learning for Medical Imaging, Algorithms, MDPI, Dec. 2009.  Official location  
• 何 立風, 巣 宇燕, Kenji Suzuki, 中村剛士, 伊藤英則. 2値画像における高速2回走査ラベル付けアルゴリズム, 画像ラボ, 日本工業出版, vol. 19, no. 9, pp. 15-19, Sept. 2008.
• Kenji Suzuki. Massive training artificial neural network (MTANN)を利用したCADの胸部診断領域への応用, 映像情報Medical, Vol. 39, No. 13, pp. 1202-1209, Dec. 2007.
• Wu K., Otoo E., Kenji Suzuki. Two Strategies to speed up connected component labeling algorithms, Lawrence Berkeley National Laboratory Tech Report, LBNL-59102, 2005.
• Kenji Suzuki. Massive Training Artificial Neural Network (MTANN): CADのための正常・異常陰影を学ぶ汎用性の高いパターン処理, 月刊インナービジョン2004年10月号, Vol. 19, No. 10, pp. 31-37, Oct. 2004.
• Kenji Suzuki. ニューラルネットワークに関する文献紹介, 画像通信, 日本放射線技術学会, Vol. 26, No. 1, pp. 48-50, Mar. 2003.
• Kenji Suzuki, 堀場勇夫. アナログ予測ニューラルネットを用いた狭窄率認識, 画像ラボ, 日本工業出版, vol. 6, no. 4, pp. 63-66, Apr. 1995.

Patent

• Kenji Suzuki. 推定装置、推定方法及びプログラム. Patent. Published. 国立大学法人東京工業大学. 2022/11/30. PCT/JP2022/044260. 2023/06/08. WO 2023/100953. 2023.
• Kenji Suzuki. 情報処理システム及び情報処理方法. Patent. Published. 国立大学法人東京工業大学. 2022/07/08. 特願2022-110448. 2024/01/19. 特開2024-008511. 2024.
• Kenji Suzuki, Ze Jin. 画像処理装置、画像処理方法及びプログラムが格納された非一時的なコンピュータ可読媒体. Patent. Published. 国立大学法人東京工業大学. 2022/03/02. PCT/JP2022/008813. 2022/09/09. WO 2022/186263. 2022.
• Kenji Suzuki, TAKASHI OBI, HIROYUKI SUZUKI. 染色画像推定器学習装置、画像処理装置、染色画像推定器学習方法、画像処理方法、染色画像推定器学習プログラム、及び、画像処理プログラム. Patent. Registered. 国立大学法人東京工業大学, 学校法人埼玉医科大学. 2019/03/06. 特願2019-041046. 2020/09/10. 特開2020-144012. 特許第7470339号. 2024/04/10 2024.

Degree

• 医用X線像のニューラル画像処理の研究,  Thesis,  Doctor (Engineering),  名古屋大学, 

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