Machine Learning in Medical Imaging

Table of Contents

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   Book Overview
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   Chapter 1 From Large to Small Organ Segmentation in CT Using Regional Context
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   Chapter 2 Motion Corruption Detection in Breast DCE-MRI
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   Chapter 3 Detection and Localization of Drosophila Egg Chambers in Microscopy Images
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   Chapter 4 Growing a Random Forest with Fuzzy Spatial Features for Fully Automatic Artery-Specific Coronary Calcium Scoring
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   Chapter 5 Atlas of Classifiers for Brain MRI Segmentation
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   Chapter 6 Dictionary Learning and Sparse Coding-Based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
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   Chapter 7 Yet Another ADNI Machine Learning Paper? Paving the Way Towards Fully-Reproducible Research on Classification of Alzheimer’s Disease
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   Chapter 8 Multi-factorial Age Estimation from Skeletal and Dental MRI Volumes
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    Chapter 9 Automatic Classification of Proximal Femur Fractures Based on Attention Models
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    Chapter 10 Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation
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    Chapter 11 Accurate and Consistent Hippocampus Segmentation Through Convolutional LSTM and View Ensemble
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    Chapter 12 STAR: Spatio-Temporal Architecture for Super-Resolution in Low-Dose CT Perfusion
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    Chapter 13 Classification of Alzheimer’s Disease by Cascaded Convolutional Neural Networks Using PET Images
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    Chapter 14 Finding Dense Supervoxel Correspondence of Cone-Beam Computed Tomography Images
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    Chapter 15 Multi-scale Volumetric ConvNet with Nested Residual Connections for Segmentation of Anterior Cranial Base
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    Chapter 16 Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-status Dementia Diagnosis
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    Chapter 17 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels
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    Chapter 18 Efficient Groupwise Registration for Brain MRI by Fast Initialization
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    Chapter 19 Sparse Multi-view Task-Centralized Learning for ASD Diagnosis
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    Chapter 20 Inter-subject Similarity Guided Brain Network Modeling for MCI Diagnosis
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    Chapter 21 Scalable and Fault Tolerant Platform for Distributed Learning on Private Medical Data
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    Chapter 22 Triple-Crossing 2.5D Convolutional Neural Network for Detecting Neuronal Arbours in 3D Microscopic Images
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    Chapter 23 Longitudinally-Consistent Parcellation of Infant Population Cortical Surfaces Based on Functional Connectivity
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    Chapter 24 Gradient Boosted Trees for Corrective Learning
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    Chapter 25 Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
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    Chapter 26 A Point Says a Lot: An Interactive Segmentation Method for MR Prostate via One-Point Labeling
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    Chapter 27 Collage CNN for Renal Cell Carcinoma Detection from CT
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    Chapter 28 Aggregating Deep Convolutional Features for Melanoma Recognition in Dermoscopy Images
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    Chapter 29 Localizing Cardiac Structures in Fetal Heart Ultrasound Video
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    Chapter 30 Deformable Registration Through Learning of Context-Specific Metric Aggregation
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    Chapter 31 Segmentation of Craniomaxillofacial Bony Structures from MRI with a 3D Deep-Learning Based Cascade Framework
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    Chapter 32 3D U-net with Multi-level Deep Supervision: Fully Automatic Segmentation of Proximal Femur in 3D MR Images
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    Chapter 33 Indecisive Trees for Classification and Prediction of Knee Osteoarthritis
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    Chapter 34 Whole Brain Segmentation and Labeling from CT Using Synthetic MR Images
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    Chapter 35 Structural Connectivity Guided Sparse Effective Connectivity for MCI Identification
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    Chapter 36 Fusion of High-Order and Low-Order Effective Connectivity Networks for MCI Classification
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    Chapter 37 Novel Effective Connectivity Network Inference for MCI Identification
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    Chapter 38 Reconstruction of Thin-Slice Medical Images Using Generative Adversarial Network
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    Chapter 39 Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to “Virtual” High-Dose CT Images
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    Chapter 40 Deep-FExt: Deep Feature Extraction for Vessel Segmentation and Centerline Prediction
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    Chapter 41 Product Space Decompositions for Continuous Representations of Brain Connectivity
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    Chapter 42 Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks
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    Chapter 43 Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
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    Chapter 44 Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks