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Deep Learning and Convolutional Neural Networks for Medical Image Computing By Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang PDF

Download Book : Deep Learning and Convolutional Neural Networks for Medical Image Computing By Le Lu, Yefeng Zheng, Gustavo Carneiro, Lin Yang PDF



Informations about the book:



Title: 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

Size: 13.7 MB

Format: PDF

Year: 2017

Pages: 300


Book Contents:




Part I Review 
1 Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective
2 Review of Deep Learning Methods in Mammography, Cardiovascular, and Microscopy Image Analysis
Part II Detection and Localization
3 Efficient False Positive Reduction in Computer-Aided Detection Using Convolutional Neural Networks and Random View Aggregation
4 Robust Landmark Detection in Volumetric Data with Efficient 3D Deep Learning
5 A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independent Set
6 Deep Learning for Histopathological Image Analysis: Towards Computerized Diagnosis on Cancers 
7 Interstitial Lung Diseases via Deep Convolutional Neural Networks: Segmentation Label Propagation, Unordered Pooling and Cross-Dataset Learning
8 Three Aspects on Using Convolutional Neural Networks for Computer-Aided Detection in Medical Imaging
9 Cell Detection with Deep Learning Accelerated by Sparse Kernel
10 Fully Convolutional Networks in Medical Imaging: Applications to Image Enhancement and Recognition
Part III Segmentation
12 Fully Automated Segmentation Using Distance Regularised Level Set and Deep-Structured Learning and Inference
13 Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms
14 Deep Learning Based Automatic Segmentation of Pathological Kidney in CT: Local Versus Global Image Context
15 Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising Autoencoders
16 Automatic Pancreas Segmentation Using Coarse-to-Fine Superpixel Labeling
Part IV Big Dataset and Text-Image Deep Mining
17 Interleaved Text/Image Deep Mining on a Large-Scale Radiology Image Database
11 On the Necessity of Fine-Tuned Convolutional Neural Networks for Medical Imaging





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