Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets (Paperback, Softcover Repri)

Part I: Review 1. Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective Ronald M. Summers 2. Review of Deep Learning Methods in Mammography, Cardiovascular and Microscopy Image Analysis Gustavo Carneiro, Yefeng Zheng, Fuyong Xing, and Lin Yang · Part II: Detection and Localization 3. Efficient False-Positive Reduction in Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation Holger R. Roth, Le Lu, Jiamin Liu, Jianhua Yao, Ari Seff, Kevin Cherry, Lauren Kim, and Ronald M. Summers 4. Robust Landmark Detection in Volumetric Data with Efficient 3D Deep Learning Yefeng Zheng, David Liu, Bogdan Georgescu, Hien Nguyen, and Dorin Comaniciu 5. A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independent Set Fujun Liu and Lin Yang 6. Deep Learning for Histopathological Image Analysis: Towards Computerized Diagnosis on Cancers Jun Xu, Chao Zhou, Bing Lang, and Qingshan Liu 7. Interstitial Lung Diseases via Deep Convolutional Neural Networks: Segmentation Label Propagation, Unordered Pooling and Cross-Dataset Learning Mingchen Gao, Ziyue Xu, Le Lu, and Daniel J. Mollura 8. Three Aspects on Using Convolutional Neural Networks for Computer-Aided Detection in Medical Imaging Hoo-Chang Shin, Holger R. Roth, Mingchen Gao, Le Lu, Ziyue Xu, Isabella Nogues, Jianhua Yao, Daniel Mollura, and Ronald M. Summers 9. Cell Detection with Deep Learning Accelerated by Sparse Kernel Junzhou Huang and Zheng Xu 10. Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition Christian Baumgartner, Ozan Oktay, and Daniel Rueckert 11. On the Necessity of Fine-Tuned Convolutional Neural Networks for Medical Imaging Nima Tajbakhsh, Jae Y. Shin, Suryakanth R. Gurudu, R. Todd Hurst, Christopher B. Kendall, Michael B. Gotway, and Jianming Liang · Part III: Segmentation 12. Fully Automated Segmentation Using Distance Regularized Level Set and Deep-Structured Learning and Inference Tuan Anh Ngo and Gustavo Carneiro 13. Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms Neeraj Dhungel, Gustavo Carneiro, and Andrew P. Bradley 14. Deep Learning Based Automatic Segmentation of Pathological Kidney in CT: Local vs. Global Image Context Yefeng Zheng, David Liu, Bogdan Georgescu, Daguang Xu, and Dorin Comaniciu 15. Robust Cell Detection and Segmentation in Histopathological Images using Sparse Reconstruction and Stacked Denoising Autoencoders Hai Su, Fuyong Xing, Xiangfei Kong, Yuanpu Xie, Shaoting Zhang and Lin Yang 16. Automatic Pancreas Segmentation Using Coarse-to-Fine Superpixel Labeling Amal Farag, Le Lu, Holger R. Roth, Jiamin Liu, Evrim Turkbey, and Ronald M. Summers · Part IV: Big Dataset and Text-Image Deep Mining 17. Interleaved Text/Image Deep Mining on a Large-Scale Radiology Image Database Hoo-Chang Shin, Le Lu, Lauren Kim, Ari Seff, Jianhua Yao, and Ronald Summers