Deep Learning for Medical Image Analysis

<p>PART 1: INTRODUCTION<br>1. An introduction to neural network and deep learning (covering CNN, RNN, RBM, Autoencoders)<br>Heung-Il Suk<br>2. An Introduction to Deep Convolutional Neural Nets for Computer Vision<br>Suraj Srinivas, Ravi K. Sarvadevabhatla, Konda R. Mopuri, Nikita Prabhu, Srinivas S.S. Kruthiventi and R. Venkatesh Babu</p> <p>PART 2: MEDICAL IMAGE DETECTION AND RECOGNITION<br>3. Efficient Medical Image Parsing<br>Florin C. Ghesu, Bogdan Georgescu and Joachim Hornegger<br>4. Multi-Instance Multi-Stage Deep Learning for Medical Image Recognition<br>Zhennan Yan, Yiqiang Zhan, Shaoting Zhang, Dimitris Metaxas and Xiang Sean Zhou<br>5. Automatic Interpretation of Carotid Intima–Media Thickness Videos Using Convolutional Neural Networks <br>Nima Tajbakhsh, Jae Y. Shin, R. Todd Hurst, Christopher B. Kendall and Jianming Liang<br>6. Deep Cascaded Networks for Sparsely Distributed Object Detection from Medical Images<br>Hao Chen, Qi Dou, Lequan Yu, Jing Qin, Lei Zhao, Vincent C.T. Mok, Defeng Wang, Lin Shi and Pheng-Ann Heng<br>7. Deep Voting and Structured Regression for Microscopy Image Analysis<br>Yuanpu Xie, Fuyong Xing and Lin Yang</p> <p>PART 3 MEDICAL IMAGE SEGMENTATION<br>8. Deep Learning Tissue Segmentation in Cardiac Histopathology Images<br>Jeffrey J. Nirschl, Andrew Janowczyk, Eliot G. Peyster, Renee Frank, Kenneth B. Margulies, Michael D. Feldman and Anant Madabhushi<br>9. Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching<br>Yanrong Guo, Yaozong Gao and Dinggang Shen<br>10. Characterization of Errors in Deep Learning-Based Brain MRI Segmentation<br>Akshay Pai, Yuan-Ching Teng, Joseph Blair, Michiel Kallenberg, Erik B. Dam, Stefan Sommer, Christian Igel and Mads Nielsen</p> <p>PART 4 MEDICAL IMAGE REGISTRATION<br>11. Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning<br>Shaoyu Wang, Minjeong Kim, Guorong Wu and Dinggang Shen<br>12. Convolutional Neural Networks for Robust and Real-Time 2-D/3-D Registration<br>Shun Miao, Jane Z. Wang and Rui Liao</p> <p>PART 5 COMPUTER-AIDED DIAGNOSIS AND DISEASE QUANTIFICATION<br>13. Chest Radiograph Pathology Categorization via Transfer Learning<br>Idit Diamant, Yaniv Bar, Ofer Geva, Lior Wolf, Gali Zimmerman, Sivan Lieberman, Eli Konen and Hayit Greenspan<br>14. Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions<br>Gustavo Carneiro, Jacinto Nascimento and Andrew P. Bradley<br>15. Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer’s Disease<br>Vamsi K. Ithapu, Vikas Singh and Sterling C. Johnson<br>16. Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis<br>Raviteja Vemulapalli, Hien Van Nguyen and S.K. Zhou<br>17. Natural Language Processing for Large-Scale Medical Image Analysis Using Deep Learning<br>Hoo-Chang Shin, Le Lu and Ronald M. Summers</p>