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Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging

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Cover of 'Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Real-Time 2D/3D Deformable Registration Using Metric Learning
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    Chapter 2 Groupwise Spectral Log-Demons Framework for Atlas Construction
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    Chapter 3 Robust Anatomical Correspondence Detection by Graph Matching with Sparsity Constraint
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    Chapter 4 Semi-supervised Segmentation Using Multiple Segmentation Hypotheses from a Single Atlas
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    Chapter 5 Carotid Artery Wall Segmentation by Coupled Surface Graph Cuts
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    Chapter 6 Graph Cut Segmentation Using a Constrained Statistical Model with Non-linear and Sparse Shape Optimization
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    Chapter 7 Novel Context Rich LoCo and GloCo Features with Local and Global Shape Constraints for Segmentation of 3D Echocardiograms with Random Forests
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    Chapter 8 Novel Vector-Valued Approach to Automatic Brain Tissue Classification
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    Chapter 9 Atlas-Based Whole-Body PET-CT Segmentation Using a Passive Contour Distance
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    Chapter 10 Spatially Aware Patch-Based Segmentation (SAPS): An Alternative Patch-Based Segmentation Framework
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    Chapter 11 Efficient Geometrical Potential Force Computation for Deformable Model Segmentation
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    Chapter 12 Shape Prior Model for Media-Adventitia Border Segmentation in IVUS Using Graph Cut
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    Chapter 13 Multiple Atlases-Based Joint Labeling of Human Cortical Sulcal Curves
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    Chapter 14 Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
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    Chapter 15 Oblique Random Forests for 3-D Vessel Detection Using Steerable Filters and Orthogonal Subspace Filtering
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    Chapter 16 Pipeline for Tracking Neural Progenitor Cells
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    Chapter 17 Automatic Heart Isolation in 3D CT Images
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    Chapter 18 Randomness and Sparsity Induced Codebook Learning with Application to Cancer Image Classification
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    Chapter 19 Context Enhanced Graphical Model for Object Localization in Medical Images
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    Chapter 20 A Cascade Learning Method for Liver Lesion Detection in CT Images
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    Chapter 21 Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
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    Chapter 22 Automatic Extraction of the Curved Midsagittal Brain Surface on MR Images
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    Chapter 23 Identification of Malignant Breast Tumors Based on Acoustic Attenuation Mapping of Conventional Ultrasound Images
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    Chapter 24 What Genes Tell about Iris Appearance
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    Chapter 25 Robust Dense Endoscopic Stereo Reconstruction for Minimally Invasive Surgery
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    Chapter 26 Model-Based Human Teeth Shape Recovery from a Single Optical Image with Unknown Illumination
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    Chapter 27 Brain Tumor Cell Density Estimation from Multi-modal MR Images Based on a Synthetic Tumor Growth Model
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    Chapter 28 Current-Based 4D Shape Analysis for the Mechanical Personalization of Heart Models
Attention for Chapter 13: Multiple Atlases-Based Joint Labeling of Human Cortical Sulcal Curves
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Chapter title
Multiple Atlases-Based Joint Labeling of Human Cortical Sulcal Curves
Chapter number 13
Book title
Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
Published by
Springer, Berlin, Heidelberg, October 2012
DOI 10.1007/978-3-642-36620-8_13
Book ISBNs
978-3-64-236619-2, 978-3-64-236620-8
Authors

Ilwoo Lyu, Gang Li, Minjeong Kim, Dinggang Shen

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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