@book{CTT100828327,
  author = {Kenji Suzuki and Liu J. and Zarshenas A. and Higaki T. and Fukumoto W. and Awai, K.},
  title = {Neural network convolution (NNC) for converting ultra-low-dose to “virtual” high-dose CT images},
  publisher = {},
  year = 2017,
}

@book{CTT100828623,
  author = {Kenji Suzuki},
  title = {Computer-aided detection of lung cancer},
  publisher = {Springer},
  year = 2017,
}

@book{CTT100828915,
  author = {Wang Qian and Shi Yinghuan and Suk Heung-Il and Kenji Suzuki},
  title = {Machine Learning in Medical Imaging (Lecture Notes in Computer Science 10541)},
  publisher = {Springer Cham},
  year = 2017,
}

@article{CTT100791217,
  author = {Kenji Suzuki},
  title = {Overview of deep learning in medical imaging},
  journal = {Radiological Physics and Technology},
  year = 2017,
}

@article{CTT100829269,
  author = {Kenji Suzuki},
  title = {Survey of Deep Learning Applications to Medical Image Analysis},
  journal = {Medical Imaging Technology},
  year = 2017,
}

@article{CTT100845096,
  author = {平野靖 and 伊藤貴佳 and 橋本典明 and 木戸尚治 and 鈴木賢治},
  title = {胸腹部コンピューター支援診断におけるMTANN深層学習},
  journal = {Medical Imaging Technology},
  year = 2017,
}

@article{CTT100829270,
  author = {Kenji SUZUKI},
  title = {Machine Learning in Medical Imaging Before and After Introduction of Deep Learning},
  journal = {Medical Imaging and Information Sciences},
  year = 2017,
}

@article{CTT100828353,
  author = {Chen, Y. and Chan, A.B. and Lin, Z. and Wang, G. and Kenji Suzuki},
  title = {Efficient tree-structured SfM by RANSAC generalized Procrustes analysis},
  journal = {Computer Vision and Image Understanding},
  year = 2017,
}

@article{CTT100885833,
  author = {Ayman El-Baz and Georgy Gimel’farb and Kenji Suzuki},
  title = {Special issue: Machine Learning Applications in Medical Image Analysis},
  journal = {Computational and Mathematical Methods in Medicine},
  year = 2017,
}

@article{CTT100885834,
  author = {Kenji Suzuki and Luping Zhou and Qian Wang},
  title = {Special issue: Machine Learning in Medical Imaging},
  journal = {Pattern Recognition},
  year = 2017,
}

@article{CTT100828354,
  author = {Huynh, H.T. and Le-Trong, N. and Bao, P.T. and Oto, A. and Kenji Suzuki},
  title = {Fully automated MR liver volumetry using watershed segmentation coupled with active contouring},
  journal = {International Journal of Computer Assisted Radiology and Surgery},
  year = 2017,
}

@article{CTT100828351,
  author = {Tajbakhsh, N. and Kenji Suzuki},
  title = {Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs},
  journal = {Pattern Recognition},
  year = 2017,
}

@article{CTT100828406,
  author = {He, L. and Zhao, X. and Yao, B. and Yang, Y. and Chao, Y. and Shi, Z. and Kenji Suzuki},
  title = {A combinational algorithm for connected-component labeling and Euler number computing},
  journal = {Journal of Real-Time Image Processing},
  year = 2017,
}

@inproceedings{CTT100844669,
  author = {Liu J. and Zarshenas A. and Wei Z. and Yang L. and Fajardo L. L. and Suzuki K.},
  title = {Virtual High-Dose (VHD) Technology: Radiation Dose Reduction in Digital Breast Tomosynthesis (DBT) by Means of Supervised Deep-Learning Image Processing (DLIP)},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844670,
  author = {Suzuki K. and Zarshenas A. and Liu J. and Zhao Y. and Luo Y.},
  title = {What Was Changed in Machine Learning (ML) in Medical Image Analysis After the Introduction of Deep Learning?},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844671,
  author = {Liu J. and Zarshenas A. and Wei Z. and Yang L. and Fajardo L. L. and Suzuki K.},
  title = {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},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844677,
  author = {Tajbakhsh N. and Zarshenas A. and Liu J. and Suzuki K.},
  title = {Two Deep-Learning Models for Lung Nodule Detection and Classification in CT: Convolutional Neural Network (CNN) vs Neural Network Convolution (NNC)},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844676,
  author = {Zarshenas A. and Zhao Y. and Liu J. and Higaki T. and Awai K. and Suzuki K.},
  title = {Radiation Dose Reduction in Thin-Slice Chest CT at a Micro-Dose (mD) Level by Means of 3D Deep Neural Network Convolution (NNC)},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844675,
  author = {Ito T. and Hirano Y. and Suzuki K. and Kido S.},
  title = {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},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844674,
  author = {Fukumoto W. and Suzuki K. and Higaki T. and Zhao Y. and Zarshenas A. and Awai K.},
  title = {Detection of Solid Pulmonary Nodules in Micro-Dose CT (mDCT) with “Virtual” Higher-Dose (vHD) CT Technology: An Observer Performance Study},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844673,
  author = {Zarshenas A. and Patel J. V. and Liu J. and Forti P. and Suzuki K.},
  title = {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)},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844678,
  author = {Tajbakhsh N. and Zarshenas A. and Liu J. and Suzuki K.},
  title = {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},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844672,
  author = {Zarshenas A. and Liu J. and Suzuki K.},
  title = {Highly Efficient Biomarker Selection (BS) Based on Novel Binary Coordinate Accent (BCA) for Machine Learning with a Large Dataset in Radiomics},
  booktitle = {},
  year = 2017,
}

@inproceedings{CTT100844668,
  author = {Tajbakhsh N. and Zarshenas A. and Liu J. and Suzuki K.},
  title = {How Deep Should We Go with Deep Learning in Medical Image Analysis?},
  booktitle = {},
  year = 2017,
}

@misc{CTT100885549,
  author = {鈴木賢治},
  title = {特集／医用画像工学分野におけるディープラーニング応用と研究開発 —序文—},
  year = 2017,
}

@misc{CTT100885596,
  author = {El-Baz A. and Gimel'farb G. and Kenji Suzuki},
  title = {Machine Learning Applications in Medical Image Analysis},
  year = 2017,
}

@misc{CTT100885597,
  author = {Kenji Suzuki and Zhou L. and Wang Q.},
  title = {Machine learning in medical imaging},
  year = 2017,
}