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Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

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Cover of 'Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support'

Table of Contents

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    Book Overview
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    Chapter 1 UNet++: A Nested U-Net Architecture for Medical Image Segmentation
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    Chapter 2 Deep Semi-supervised Segmentation with Weight-Averaged Consistency Targets
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    Chapter 3 Handling Missing Annotations for Semantic Segmentation with Deep ConvNets
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    Chapter 4 A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data
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    Chapter 5 Multi-scale Residual Network with Two Channels of Raw CT Image and Its Differential Excitation Component for Emphysema Classification
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    Chapter 6 TreeNet: Multi-loss Deep Learning Network to Predict Branch Direction for Extracting 3D Anatomical Trees
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    Chapter 7 3D Deep Affine-Invariant Shape Learning for Brain MR Image Segmentation
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    Chapter 8 Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography
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    Chapter 9 MTMR-Net: Multi-task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis
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    Chapter 10 Active Deep Learning with Fisher Information for Patch-Wise Semantic Segmentation
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    Chapter 11 Contextual Additive Networks to Efficiently Boost 3D Image Segmentations
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    Chapter 12 Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration
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    Chapter 13 Rapid Training Data Generation for Tissue Segmentation Using Global Approximate Block-Matching with Self-organizing Maps
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    Chapter 14 Focal Dice Loss and Image Dilation for Brain Tumor Segmentation
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    Chapter 15 Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning
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    Chapter 16 3D Convolutional Neural Networks for Classification of Functional Connectomes
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    Chapter 17 Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks
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    Chapter 18 Unpaired Deep Cross-Modality Synthesis with Fast Training
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    Chapter 19 UOLO - Automatic Object Detection and Segmentation in Biomedical Images
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    Chapter 20 Unpaired Brain MR-to-CT Synthesis Using a Structure-Constrained CycleGAN
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    Chapter 21 Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy
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    Chapter 22 Weakly Supervised Localisation for Fetal Ultrasound Images
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    Chapter 23 PIMMS: Permutation Invariant Multi-modal Segmentation
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    Chapter 24 Unsupervised Feature Learning for Outlier Detection with Stacked Convolutional Autoencoders, Siamese Networks and Wasserstein Autoencoders: Application to Epilepsy Detection
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    Chapter 25 Semi-automated Extraction of Crohns Disease MR Imaging Markers Using a 3D Residual CNN with Distance Prior
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    Chapter 26 Learning Optimal Deep Projection of $$^{18}$$ F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes
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    Chapter 27 Learning to Segment Medical Images with Scribble-Supervision Alone
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    Chapter 28 Learning to Decode 7T-Like MR Image Reconstruction from 3T MR Images
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    Chapter 29 Nonlinear Adaptively Learned Optimization for Object Localization in 3D Medical Images
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    Chapter 30 SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays
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    Chapter 31 Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification
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    Chapter 32 Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network
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    Chapter 33 Computed Tomography Image Enhancement Using 3D Convolutional Neural Network
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    Chapter 34 Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks
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    Chapter 35 Automatic Myocardial Strain Imaging in Echocardiography Using Deep Learning
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    Chapter 36 Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images
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    Chapter 37 Longitudinal Detection of Radiological Abnormalities with Time-Modulated LSTM
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    Chapter 38 Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease
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    Chapter 39 ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans
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    Chapter 40 A Multi-scale Multiple Sclerosis Lesion Change Detection in a Multi-sequence MRI
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    Chapter 41 Multi-task Sparse Low-Rank Learning for Multi-classification of Parkinson’s Disease
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    Chapter 42 Optic Disc Segmentation in Retinal Fundus Images Using Fully Convolutional Network and Removal of False-Positives Based on Shape Features
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    Chapter 43 Integrating Deformable Modeling with 3D Deep Neural Network Segmentation
Attention for Chapter 9: MTMR-Net: Multi-task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis
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Chapter title
MTMR-Net: Multi-task Deep Learning with Margin Ranking Loss for Lung Nodule Analysis
Chapter number 9
Book title
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-00889-5_9
Book ISBNs
978-3-03-000888-8, 978-3-03-000889-5
Authors

Lihao Liu, Qi Dou, Hao Chen, Iyiola E. Olatunji, Jing Qin, Pheng-Ann Heng, Liu, Lihao, Dou, Qi, Chen, Hao, Olatunji, Iyiola E., Qin, Jing, Heng, Pheng-Ann

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 16%
Student > Master 2 6%
Student > Ph. D. Student 2 6%
Student > Doctoral Student 1 3%
Professor 1 3%
Other 2 6%
Unknown 19 59%
Readers by discipline Count As %
Computer Science 5 16%
Medicine and Dentistry 4 13%
Engineering 1 3%
Design 1 3%
Unknown 21 66%