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Machine Learning in Medical Imaging

Overview of attention for book
Cover of 'Machine Learning in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI
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    Chapter 2 Error Attention Interactive Segmentation of Medical Image Through Matting and Fusion
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    Chapter 3 A Novel fMRI Representation Learning Framework with GAN
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    Chapter 4 Semi-supervised Segmentation with Self-training Based on Quality Estimation and Refinement
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    Chapter 5 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies
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    Chapter 6 Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-scale Generative Adversarial Network
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    Chapter 7 Self-recursive Contextual Network for Unsupervised 3D Medical Image Registration
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    Chapter 8 Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy
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    Chapter 9 Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows
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    Chapter 10 Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest
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    Chapter 11 A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation
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    Chapter 12 Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network
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    Chapter 13 Robust Multiple Sclerosis Lesion Inpainting with Edge Prior
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    Chapter 14 Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation
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    Chapter 15 GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes
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    Chapter 16 Anatomy-Aware Cardiac Motion Estimation
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    Chapter 17 Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation
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    Chapter 18 LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI
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    Chapter 19 Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation
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    Chapter 20 Boundary-Aware Network for Kidney Tumor Segmentation
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    Chapter 21 O-Net: An Overall Convolutional Network for Segmentation Tasks
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    Chapter 22 Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints
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    Chapter 23 EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis
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    Chapter 24 Deep Distance Map Regression Network with Shape-Aware Loss for Imbalanced Medical Image Segmentation
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    Chapter 25 Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer
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    Chapter 26 Exploring Functional Difference Between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks
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    Chapter 27 Detection of Ischemic Infarct Core in Non-contrast Computed Tomography
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    Chapter 28 Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers
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    Chapter 29 Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients
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    Chapter 30 Structural Connectivity Enriched Functional Brain Network Using Simplex Regression with GraphNet
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    Chapter 31 Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification
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    Chapter 32 Multi-tasking Siamese Networks for Breast Mass Detection Using Dual-View Mammogram Matching
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    Chapter 33 3D Volume Reconstruction from Single Lateral X-Ray Image via Cross-Modal Discrete Embedding Transition
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    Chapter 34 Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks
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    Chapter 35 A Deep Network for Joint Registration and Reconstruction of Images with Pathologies
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    Chapter 36 Learning Conditional Deformable Shape Templates for Brain Anatomy
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    Chapter 37 Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity
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    Chapter 38 Unsupervised Learning for Spherical Surface Registration
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    Chapter 39 Anatomy-Guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI
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    Chapter 40 Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization
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    Chapter 41 Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors
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    Chapter 42 Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening
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    Chapter 43 Importance Driven Continual Learning for Segmentation Across Domains
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    Chapter 44 RDCNet: Instance Segmentation with a Minimalist Recurrent Residual Network
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    Chapter 45 Automatic Segmentation of Achilles Tendon Tissues Using Deep Convolutional Neural Network
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    Chapter 46 An End to End System for Measuring Axon Growth
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    Chapter 47 Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA
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    Chapter 48 Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling
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    Chapter 49 Unsupervised Learning-Based Nonrigid Registration of High Resolution Histology Images
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    Chapter 50 Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images
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    Chapter 51 Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation
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    Chapter 52 Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation
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    Chapter 53 Mammographic Image Conversion Between Source and Target Acquisition Systems Using cGAN
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    Chapter 54 An End-to-End Learnable Flow Regularized Model for Brain Tumor Segmentation
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    Chapter 55 Neural Architecture Search for Microscopy Cell Segmentation
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    Chapter 56 Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection
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    Chapter 57 Predicting Catheter Ablation Outcomes with Pre-ablation Heart Rhythm Data: Less Is More
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    Chapter 58 AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets
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    Chapter 59 Cross-Task Representation Learning for Anatomical Landmark Detection
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    Chapter 60 Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks
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    Chapter 61 Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation
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    Chapter 62 Open-Set Recognition for Skin Lesions Using Dermoscopic Images
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    Chapter 63 End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images
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    Chapter 64 Enhanced MRI Reconstruction Network Using Neural Architecture Search
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    Chapter 65 Learning Invariant Feature Representation to Improve Generalization Across Chest X-Ray Datasets
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    Chapter 66 Noise-Aware Standard-Dose PET Reconstruction Using General and Adaptive Robust Loss
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    Chapter 67 Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation
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    Chapter 68 Informative Feature-Guided Siamese Network for Early Diagnosis of Autism
Attention for Chapter 67: Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation
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Chapter title
Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation
Chapter number 67
Book title
Machine Learning in Medical Imaging
Published by
Springer, Cham, September 2020
DOI 10.1007/978-3-030-59861-7_67
Pubmed ID
33598664
Book ISBNs
978-3-03-059860-0, 978-3-03-059861-7
Authors

Yue Sun, Kun Gao, Sijie Niu, Weili Lin, Gang Li, Li Wang, The UNC/UMN Baby Connectome Project Consortium, Sun, Yue, Gao, Kun, Niu, Sijie, Lin, Weili, Li, Gang, Wang, Li

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 13%
Student > Ph. D. Student 1 13%
Other 1 13%
Student > Postgraduate 1 13%
Unknown 4 50%
Readers by discipline Count As %
Unspecified 1 13%
Computer Science 1 13%
Engineering 1 13%
Unknown 5 63%

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