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Medical Image Computing and Computer Assisted Intervention − MICCAI 2017

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Cover of 'Medical Image Computing and Computer Assisted Intervention − MICCAI 2017'

Table of Contents

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    Book Overview
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    Chapter 1 The Active Atlas: Combining 3D Anatomical Models with Texture Detectors
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    Chapter 2 Exploring Gyral Patterns of Infant Cortical Folding Based on Multi-view Curvature Information
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    Chapter 3 Holistic Mapping of Striatum Surfaces in the Laplace-Beltrami Embedding Space
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    Chapter 4 Novel Local Shape-Adaptive Gyrification Index with Application to Brain Development
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    Chapter 5 Joint Sparse and Low-Rank Regularized Multi-Task Multi-Linear Regression for Prediction of Infant Brain Development with Incomplete Data
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    Chapter 6 Graph-Constrained Sparse Construction of Longitudinal Diffusion-Weighted Infant Atlases
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    Chapter 7 4D Infant Cortical Surface Atlas Construction Using Spherical Patch-Based Sparse Representation
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    Chapter 8 Developmental Patterns Based Individualized Parcellation of Infant Cortical Surface
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    Chapter 9 Longitudinal Modeling of Multi-modal Image Contrast Reveals Patterns of Early Brain Growth
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    Chapter 10 Prediction of Brain Network Age and Factors of Delayed Maturation in Very Preterm Infants
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    Chapter 11 Falx Cerebri Segmentation via Multi-atlas Boundary Fusion
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    Chapter 12 A 3D Femoral Head Coverage Metric for Enhanced Reliability in Diagnosing Hip Dysplasia
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    Chapter 13 Learning-Based Multi-atlas Segmentation of the Lungs and Lobes in Proton MR Images
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    Chapter 14 Unsupervised Discovery of Spatially-Informed Lung Texture Patterns for Pulmonary Emphysema: The MESA COPD Study
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    Chapter 15 Automatic Landmark Estimation for Adolescent Idiopathic Scoliosis Assessment Using BoostNet
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    Chapter 16 Nonlinear Statistical Shape Modeling for Ankle Bone Segmentation Using a Novel Kernelized Robust PCA
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    Chapter 17 Adaptable Landmark Localisation: Applying Model Transfer Learning to a Shape Model Matching System
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    Chapter 18 Representative Patch-based Active Appearance Models Generated from Small Training Populations
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    Chapter 19 Integrating Statistical Prior Knowledge into Convolutional Neural Networks
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    Chapter 20 Statistical Shape Model of Nested Structures Based on the Level Set
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    Chapter 21 Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans
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    Chapter 22 Learning Deep Features for Automated Placement of Correspondence Points on Ensembles of Complex Shapes
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    Chapter 23 Robust Multi-scale Anatomical Landmark Detection in Incomplete 3D-CT Data
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    Chapter 24 Learning and Incorporating Shape Models for Semantic Segmentation
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    Chapter 25 Surface-Wise Texture Patch Analysis of Combined MRI and PET to Detect MRI-Negative Focal Cortical Dysplasia
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    Chapter 26 Training CNNs for Image Registration from Few Samples with Model-based Data Augmentation
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    Chapter 27 Nonrigid Image Registration Using Multi-scale 3D Convolutional Neural Networks
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    Chapter 28 Multimodal Image Registration with Deep Context Reinforcement Learning
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    Chapter 29 Directional Averages for Motion Segmentation in Discontinuity Preserving Image Registration
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    Chapter 30 $$\ell _2$$ Similarity Metrics for Diffusion Multi-Compartment Model Images Registration
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    Chapter 31 SVF-Net: Learning Deformable Image Registration Using Shape Matching
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    Chapter 32 A Large Deformation Diffeomorphic Approach to Registration of CLARITY Images via Mutual Information
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    Chapter 33 Mixed Metric Random Forest for Dense Correspondence of Cone-Beam Computed Tomography Images
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    Chapter 34 Optimal Transport for Diffeomorphic Registration
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    Chapter 35 Deformable Image Registration Based on Similarity-Steered CNN Regression
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    Chapter 36 Generalised Coherent Point Drift for Group-Wise Registration of Multi-dimensional Point Sets
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    Chapter 37 Fast Geodesic Regression for Population-Based Image Analysis
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    Chapter 38 Deformable Registration of a Preoperative 3D Liver Volume to a Laparoscopy Image Using Contour and Shading Cues
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    Chapter 39 Parameter Sensitivity Analysis in Medical Image Registration Algorithms Using Polynomial Chaos Expansions
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    Chapter 40 Robust Non-rigid Registration Through Agent-Based Action Learning
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    Chapter 41 Selecting the Optimal Sequence for Deformable Registration of Microscopy Image Sequences Using Two-Stage MST-based Clustering Algorithm
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    Chapter 42 Dynamic Regression for Partial Correlation and Causality Analysis of Functional Brain Networks
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    Chapter 43 Kernel-Regularized ICA for Computing Functional Topography from Resting-State fMRI
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    Chapter 44 N-way Decomposition: Towards Linking Concurrent EEG and fMRI Analysis During Natural Stimulus
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    Chapter 45 Connectome-Based Pattern Learning Predicts Histology and Surgical Outcome of Epileptogenic Malformations of Cortical Development
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    Chapter 46 Joint Representation of Connectome-Scale Structural and Functional Profiles for Identification of Consistent Cortical Landmarks in Human Brains
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    Chapter 47 Subject-Specific Structural Parcellations Based on Randomized AB-divergences
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    Chapter 48 Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors
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    Chapter 49 Multi-way Regression Reveals Backbone of Macaque Structural Brain Connectivity in Longitudinal Datasets
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    Chapter 50 Multimodal Hyper-connectivity Networks for MCI Classification
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    Chapter 51 Multi-modal EEG and fMRI Source Estimation Using Sparse Constraints
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    Chapter 52 Statistical Learning of Spatiotemporal Patterns from Longitudinal Manifold-Valued Networks
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    Chapter 53 Population-Shrinkage of Covariance to Estimate Better Brain Functional Connectivity
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    Chapter 54 Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks
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    Chapter 55 A Submodular Approach to Create Individualized Parcellations of the Human Brain
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    Chapter 56 BrainSync: An Orthogonal Transformation for Synchronization of fMRI Data Across Subjects
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    Chapter 57 Supervised Discriminative EEG Brain Source Imaging with Graph Regularization
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    Chapter 58 Inference and Visualization of Information Flow in the Visual Pathway Using dMRI and EEG
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    Chapter 59 Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification
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    Chapter 60 Dynamic Field Mapping and Motion Correction Using Interleaved Double Spin-Echo Diffusion MRI
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    Chapter 61 A Novel Anatomically-Constrained Global Tractography Approach to Monitor Sharp Turns in Gyri
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    Chapter 62 Learn to Track: Deep Learning for Tractography
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    Chapter 63 FiberNET: An Ensemble Deep Learning Framework for Clustering White Matter Fibers
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    Chapter 64 Supra-Threshold Fiber Cluster Statistics for Data-Driven Whole Brain Tractography Analysis
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    Chapter 65 White Matter Fiber Representation Using Continuous Dictionary Learning
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    Chapter 66 Fiber Orientation Estimation Guided by a Deep Network
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    Chapter 67 FOD Restoration for Enhanced Mapping of White Matter Lesion Connectivity
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    Chapter 68 Learning-Based Ensemble Average Propagator Estimation
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    Chapter 69 A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI
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    Chapter 70 Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
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    Chapter 71 q-Space Upsampling Using x-q Space Regularization
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    Chapter 72 Neighborhood Matching for Curved Domains with Application to Denoising in Diffusion MRI
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    Chapter 73 Gray Matter Surface Based Spatial Statistics (GS-BSS) in Diffusion Microstructure
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    Chapter 74 A Bag-of-Features Approach to Predicting TMS Language Mapping Results from DSI Tractography
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    Chapter 75 Patient-Specific Skeletal Muscle Fiber Modeling from Structure Tensor Field of Clinical CT Images
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    Chapter 76 Revealing Hidden Potentials of the q-Space Signal in Breast Cancer
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    Chapter 77 Denoising Moving Heart Wall Fibers Using Cartan Frames
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    Chapter 78 TBS: Tensor-Based Supervoxels for Unfolding the Heart
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    Chapter 79 A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
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    Chapter 80 Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)
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    Chapter 81 Towards Automatic Semantic Segmentation in Volumetric Ultrasound
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    Chapter 82 Automatic Quality Control of Cardiac MRI Segmentation in Large-Scale Population Imaging
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    Chapter 83 Towards Image-Guided Pancreas and Biliary Endoscopy: Automatic Multi-organ Segmentation on Abdominal CT with Dense Dilated Networks
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    Chapter 84 Holistic Segmentation of Intermuscular Adipose Tissues on Thigh MRI
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    Chapter 85 Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images
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    Chapter 86 Unbiased Shape Compactness for Segmentation
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    Chapter 87 Joint Reconstruction and Segmentation of 7T-like MR Images from 3T MRI Based on Cascaded Convolutional Neural Networks
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    Chapter 88 Development of a $$\upmu $$ CT-based Patient-Specific Model of the Electrically Stimulated Cochlea
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    Chapter 89 Compresso: Efficient Compression of Segmentation Data for Connectomics
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    Chapter 90 Combining Spatial and Non-spatial Dictionary Learning for Automated Labeling of Intra-ventricular Hemorrhage in Neonatal Brain MRI
Attention for Chapter 80: Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)
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Chapter title
Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels)
Chapter number 80
Book title
Medical Image Computing and Computer Assisted Intervention − MICCAI 2017
Published by
Springer, Cham, September 2017
DOI 10.1007/978-3-319-66182-7_80
Book ISBNs
978-3-31-966181-0, 978-3-31-966182-7

Lin Gu, Yinqiang Zheng, Ryoma Bise, Imari Sato, Nobuaki Imanishi, Sadakazu Aiso

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 18%
Student > Bachelor 7 18%
Student > Master 5 13%
Other 2 5%
Researcher 2 5%
Other 4 11%
Unknown 11 29%
Readers by discipline Count As %
Computer Science 19 50%
Engineering 6 16%
Unspecified 1 3%
Unknown 12 32%