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Deep learning and convolutional neural networks for medical image computing : precision medicine, high performance and large-scale datasets

Author: Le Lu; Yefeng Zheng; Gustavo Carneiro; Lin Yang, (inżynieria biomedyczna).; Springer Science+Business Media.
Publisher: Cham : Springer International Publishing Switzerland, 2017.
Series: Advances in Computer Vision and Pattern Recognition.
Edition/Format:   Print book : EnglishView all editions and formats
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This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database  Read more...

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Document Type: Book
All Authors / Contributors: Le Lu; Yefeng Zheng; Gustavo Carneiro; Lin Yang, (inżynieria biomedyczna).; Springer Science+Business Media.
ISBN: 9783319429984 3319429981 9783319429991 331942999X
OCLC Number: 1014063151
Description: XXIII [1], 326 s. : il. (w tym kolor.) ; 25 cm.
Contents: Part I: Review 1. Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective Ronald M. Summers2. Review of Deep Learning Methods in Mammography, Cardiovascular and Microscopy Image AnalysisGustavo Carneiro, Yefeng Zheng, Fuyong Xing, and Lin Yang* Part II: Detection and Localization3. 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. Summers4. Robust Landmark Detection in Volumetric Data with Efficient 3D Deep Learning Yefeng Zheng, David Liu, Bogdan Georgescu, Hien Nguyen, and Dorin Comaniciu5. A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independent Set Fujun Liu and Lin Yang6. Deep Learning for Histopathological Image Analysis: Towards Computerized Diagnosis on Cancers Jun Xu, Chao Zhou, Bing Lang, and Qingshan Liu7. 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. Mollura8. 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. Summers9. Cell Detection with Deep Learning Accelerated by Sparse Kernel Junzhou Huang and Zheng Xu10. Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition Christian Baumgartner, Ozan Oktay, and Daniel Rueckert11. 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: Segmentation12. Fully Automated Segmentation Using Distance Regularized Level Set and Deep-Structured Learning and Inference Tuan Anh Ngo and Gustavo Carneiro13. Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms Neeraj Dhungel, Gustavo Carneiro, and Andrew P. Bradley14. 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 Comaniciu15. 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 Yang16. 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 Mining17. 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
Series Title: Advances in Computer Vision and Pattern Recognition.
Responsibility: Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang editors.

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