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ORCIDDeep Learning for Medical Image Analysis, 1st Edition, 2017
- Shaohua Kevin Zhou, Hayit Greenspan, Dinggang Shen:
Deep Learning for Medical Image Analysis, 1st Edition. Academic Press 2017, ISBN 978-0-12-810408-8 - Front Matter.
- Copyright.
- Contributors.
- About the Editors.
- Nicholas Ayache:
Foreword.
Part I: Introduction
- Heung-Il Suk
:
An Introduction to Neural Networks and Deep Learning. 3-24 - Suraj Srinivas, Ravi Kiran Sarvadevabhatla, Konda Reddy Mopuri, Nikita Prabhu, Srinivas S. S. Kruthiventi, R. Venkatesh Babu:
An Introduction to Deep Convolutional Neural Nets for Computer Vision. 25-52
Part II: Medical Image Detection and Recognition
- Florin C. Ghesu, Bogdan Georgescu, Joachim Hornegger:
Efficient Medical Image Parsing. 55-81 - Zhennan Yan, Yiqiang Zhan, Shaoting Zhang, Dimitris N. Metaxas, Xiang Sean Zhou:
Multi-Instance Multi-Stage Deep Learning for Medical Image Recognition. 83-104 - Nima Tajbakhsh, Jae Y. Shin, R. Todd Hurst, Christopher B. Kendall, Jianming Liang:
Automatic Interpretation of Carotid Intima-Media Thickness Videos Using Convolutional Neural Networks. 105-131 - Hao Chen, Qi Dou, Lequan Yu, Jing Qin, Lei Zhao, Vincent C. T. Mok, Defeng Wang, Lin Shi, Pheng-Ann Heng:
Deep Cascaded Networks for Sparsely Distributed Object Detection from Medical Images. 133-154 - Yuanpu Xie, Fuyong Xing, Lin Yang:
Deep Voting and Structured Regression for Microscopy Image Analysis. 155-175
Part III: Medical Image Segmentation
- Jeffrey J. Nirschl, Andrew Janowczyk, Eliot G. Peyster, Renee Frank, Kenneth B. Margulies, Michael D. Feldman, Anant Madabhushi:
Deep Learning Tissue Segmentation in Cardiac Histopathology Images. 179-195 - Yanrong Guo, Yaozong Gao, Dinggang Shen:
Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching. 197-222 - Akshay Pai, Yuan-Ching Teng, Joseph Blair, Michiel Kallenberg, Erik B. Dam, Stefan Sommer, Christian Igel, Mads Nielsen:
Characterization of Errors in Deep Learning-Based Brain MRI Segmentation. 223-242
Part IV: Medical Image Registration
- Shaoyu Wang, Minjeong Kim, Guorong Wu, Dinggang Shen:
Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning. 245-269 - Shun Miao, Z. Jane Wang, Rui Liao:
Convolutional Neural Networks for Robust and Real-Time 2-D/3-D Registration. 271-296
Part V: Computer-Aided Diagnosis and Disease Quantification
- Idit Diamant, Yaniv Bar, Ofer Geva, Lior Wolf, Gali Zimmerman, Sivan Lieberman, Eli Konen, Hayit Greenspan:
Chest Radiograph Pathology Categorization via Transfer Learning. 299-320 - Gustavo Carneiro, Jacinto C. Nascimento, Andrew P. Bradley:
Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1. 321-339 - Vamsi K. Ithapu, Vikas Singh, Sterling C. Johnson:
Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer's Disease. 341-378
Part VI: Others
- Raviteja Vemulapalli, Hien Van Nguyen, Shaohua Kevin Zhou:
Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis. 381-403 - Hoo-Chang Shin, Le Lu, Ronald M. Summers:
Natural Language Processing for Large-Scale Medical Image Analysis Using Deep Learning. 405-421 - Index. 423-433
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