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Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017

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Table of Contents

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    Book Overview
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    Chapter 1 Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status
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    Chapter 2 Nonlinear Feature Space Transformation to Improve the Prediction of MCI to AD Conversion
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    Chapter 3 Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection
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    Chapter 4 Latent Processes Governing Neuroanatomical Change in Aging and Dementia
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    Chapter 5 A Multi-armed Bandit to Smartly Select a Training Set from Big Medical Data
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    Chapter 6 Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease
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    Chapter 7 An Unbiased Penalty for Sparse Classification with Application to Neuroimaging Data
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    Chapter 8 Unsupervised Feature Learning for Endomicroscopy Image Retrieval
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    Chapter 9 Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data
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    Chapter 10 Liver Tissue Classification in Patients with Hepatocellular Carcinoma by Fusing Structured and Rotationally Invariant Context Representation
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    Chapter 11 DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI
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    Chapter 12 Supervised Intra-embedding of Fisher Vectors for Histopathology Image Classification
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    Chapter 13 GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
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    Chapter 14 MRI-Based Surgical Planning for Lumbar Spinal Stenosis
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    Chapter 15 Pattern Visualization and Recognition Using Tensor Factorization for Early Differential Diagnosis of Parkinsonism
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    Chapter 16 Physiological Parameter Estimation from Multispectral Images Unleashed
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    Chapter 17 Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volume Modeling
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    Chapter 18 Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble
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    Chapter 19 Classification of Major Depressive Disorder via Multi-site Weighted LASSO Model
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    Chapter 20 A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification
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    Chapter 21 Spectral Graph Convolutions for Population-Based Disease Prediction
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    Chapter 22 Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation
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    Chapter 23 Sparse Multi-kernel Based Multi-task Learning for Joint Prediction of Clinical Scores and Biomarker Identification in Alzheimer’s Disease
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    Chapter 24 Personalized Diagnosis for Alzheimer’s Disease
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    Chapter 25 GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network
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    Chapter 26 Deep Supervision for Pancreatic Cyst Segmentation in Abdominal CT Scans
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    Chapter 27 Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
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    Chapter 28 Direct Detection of Pixel-Level Myocardial Infarction Areas via a Deep-Learning Algorithm
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    Chapter 29 Skin Disease Recognition Using Deep Saliency Features and Multimodal Learning of Dermoscopy and Clinical Images
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    Chapter 30 Boundary Regularized Convolutional Neural Network for Layer Parsing of Breast Anatomy in Automated Whole Breast Ultrasound
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    Chapter 31 Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection
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    Chapter 32 Full Quantification of Left Ventricle via Deep Multitask Learning Network Respecting Intra- and Inter-Task Relatedness
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    Chapter 33 Scalable Multimodal Convolutional Networks for Brain Tumour Segmentation
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    Chapter 34 Pathological OCT Retinal Layer Segmentation Using Branch Residual U-Shape Networks
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    Chapter 35 Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes
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    Chapter 36 Semi-supervised Deep Learning for Fully Convolutional Networks
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    Chapter 37 TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References
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    Chapter 38 BRIEFnet: Deep Pancreas Segmentation Using Binary Sparse Convolutions
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    Chapter 39 Supervised Action Classifier: Approaching Landmark Detection as Image Partitioning
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    Chapter 40 Robust Multi-modal MR Image Synthesis
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    Chapter 41 Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
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    Chapter 42 Clinical Target-Volume Delineation in Prostate Brachytherapy Using Residual Neural Networks
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    Chapter 43 Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography
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    Chapter 44 Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis
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    Chapter 45 Synergistic Combination of Learned and Hand-Crafted Features for Prostate Lesion Classification in Multiparametric Magnetic Resonance Imaging
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    Chapter 46 Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
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    Chapter 47 Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images
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    Chapter 48 Medical Image Synthesis with Context-Aware Generative Adversarial Networks
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    Chapter 49 Joint Detection and Diagnosis of Prostate Cancer in Multi-parametric MRI Based on Multimodal Convolutional Neural Networks
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    Chapter 50 SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging
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    Chapter 51 X-Ray In-Depth Decomposition: Revealing the Latent Structures
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    Chapter 52 Fast Prospective Detection of Contrast Inflow in X-ray Angiograms with Convolutional Neural Network and Recurrent Neural Network
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    Chapter 53 Quantification of Metabolites in Magnetic Resonance Spectroscopic Imaging Using Machine Learning
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    Chapter 54 Building Disease Detection Algorithms with Very Small Numbers of Positive Samples
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    Chapter 55 Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis
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    Chapter 56 Deep Convolutional Encoder-Decoders for Prostate Cancer Detection and Classification
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    Chapter 57 Deep Image-to-Image Recurrent Network with Shape Basis Learning for Automatic Vertebra Labeling in Large-Scale 3D CT Volumes
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    Chapter 58 Automatic Liver Segmentation Using an Adversarial Image-to-Image Network
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    Chapter 59 Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation
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    Chapter 60 Retinal Microaneurysm Detection Using Clinical Report Guided Multi-sieving CNN
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    Chapter 61 Lesion Detection and Grading of Diabetic Retinopathy via Two-Stages Deep Convolutional Neural Networks
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    Chapter 62 Hashing with Residual Networks for Image Retrieval
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    Chapter 63 Deep Multiple Instance Hashing for Scalable Medical Image Retrieval
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    Chapter 64 Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks
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    Chapter 65 Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules
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    Chapter 66 Liver Lesion Detection Based on Two-Stage Saliency Model with Modified Sparse Autoencoder
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    Chapter 67 Manifold Learning of COPD
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    Chapter 68 Hybrid Mass Detection in Breast MRI Combining Unsupervised Saliency Analysis and Deep Learning
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    Chapter 69 Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification
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    Chapter 70 Segmentation-Free Kidney Localization and Volume Estimation Using Aggregated Orthogonal Decision CNNs
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    Chapter 71 Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images
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    Chapter 72 Automated Pulmonary Nodule Detection via 3D ConvNets with Online Sample Filtering and Hybrid-Loss Residual Learning
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    Chapter 73 CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance
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    Chapter 74 Intra-perinodular Textural Transition (Ipris): A 3D Descriptor for Nodule Diagnosis on Lung CT
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    Chapter 75 Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT
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    Chapter 76 Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI
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    Chapter 77 Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks
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    Chapter 78 Modeling Cognitive Trends in Preclinical Alzheimer’s Disease (AD) via Distributions over Permutations
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    Chapter 79 Does Manual Delineation only Provide the Side Information in CT Prostate Segmentation?
Attention for Chapter 20: A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification
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Chapter title
A Multi-atlas Approach to Region of Interest Detection for Medical Image Classification
Chapter number 20
Book title
Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017
Published by
Springer, Cham, September 2017
DOI 10.1007/978-3-319-66179-7_20
Book ISBNs
978-3-31-966178-0, 978-3-31-966179-7

Hongzhi Wang, Mehdi Moradi, Yaniv Gur, Prasanth Prasanna, Tanveer Syeda-Mahmood

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 %
Researcher 3 38%
Professor > Associate Professor 1 13%
Other 1 13%
Student > Master 1 13%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Agricultural and Biological Sciences 1 13%
Engineering 1 13%
Unknown 3 38%