"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"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)",,,,,,2018,Nov.
"Luc Bidaut,Kenji Suzuki","Special Issue: Computer-Aided Diagnosis and Characterization of Diseases",,"Diagnostics","MDPI",,,,2018,Sept.
"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",,,2018,July
"鈴木賢治","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",2018,July
"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)",,,,,2018,July
"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)",,,,,2018,July
"鈴木賢治","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",2018,July
"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",,,2018,Feb.
"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",,,2018,Feb.
"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",,,2018,Feb.
"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",2018,Jan.
"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",,,,2018,Jan.
"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",2018,Jan.
"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,