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Abdominal Imaging. Computational and Clinical Applications

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Cover of 'Abdominal Imaging. Computational and Clinical Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Abdominal Imaging. Computational and Clinical Applications
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    Chapter 2 Dual-Energy Electronic Cleansing for Artifact-Free Visualization of the Colon in Fecal-Tagging CT Colonography
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    Chapter 3 Computer-Aided Polyp Detection for Laxative-Free CT Colonography
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    Chapter 4 Comparative Performance of Random Forest and Support Vector Machine Classifiers for Detection of Colorectal Lesions in CT Colonography
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    Chapter 5 Image-Enhanced Capsule Endoscopy Preserving the Original Color Tones
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    Chapter 6 3D Non-rigid Motion Correction of Free-Breathing Abdominal DCE-MRI Data
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    Chapter 7 Segmentation of Liver Tumor Using Efficient Global Optimal Tree Metrics Graph Cuts
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    Chapter 8 Ensemble Detection of Colorectal Lesions for CT Colonography
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    Chapter 9 Automated Detection of Colorectal Lesions in Non-cathartic CT Colonography
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    Chapter 10 Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy
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    Chapter 11 Automated Detection and Diagnosis of Crohn’s Disease in CT Enterography
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    Chapter 12 Quantitative Evaluation of Lumbar Disc Herniation Based on MRI Image
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    Chapter 13 Liver Tumor Segmentation Using Kernel-Based FGCM and PGCM
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    Chapter 14 Improving Diagnosis and Intervention: A Complete Approach for Registration of Liver CT Data
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    Chapter 15 Abdominal Images Non-rigid Registration Using Local-Affine Diffeomorphic Demons
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    Chapter 16 FIST: Fast Interactive Segmentation of Tumors
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    Chapter 17 Intraoperative Registration for Liver Tumor Ablation
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    Chapter 18 Sliding Geometries in Deformable Image Registration
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    Chapter 19 Simulation of Portal Vein Clamping and the Impact of Safety Margins for Liver Resection Planning
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    Chapter 20 Liver Segmentation in CT Images for Intervention Using a Graph-Cut Based Model
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    Chapter 21 Anatomical Feature-Guided Mutual Information Registration of Multimodal Prostate MRI
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    Chapter 22 Abdominal Multi-Organ Segmentation of CT Images Based on Hierarchical Spatial Modeling of Organ Interrelations
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    Chapter 23 Organ Segmentation from 3D Abdominal CT Images Based on Atlas Selection and Graph Cut
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    Chapter 24 Liver Segmental Anatomy and Analysis from Vessel and Tumor Segmentation via Optimized Graph Cuts
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    Chapter 25 Liver and Tumor Segmentation and Analysis from CT of Diseased Patients via a Generic Affine Invariant Shape Parameterization and Graph Cuts
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    Chapter 26 A Bayesian Framework for Estimating Respiratory Liver Motion from Sparse Measurements
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    Chapter 27 Semi–automated Subcutaneous and Visceral Adipose Tissue Quantification in Computed Tomography
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    Chapter 28 Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs
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    Chapter 29 Discontinuity Preserving Registration of Abdominal MR Images with Apparent Sliding Organ Motion
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    Chapter 30 Segmentation of Cervical Images by Inter-subject Registration with a Statistical Organ Model
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    Chapter 31 A New Method for Contour Determination of the Prostate in Ultrasound Images
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    Chapter 32 Analyses of Missing Organs in Abdominal Multi-Organ Segmentation
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    Chapter 33 Geometric Modelling of Patient-Specific Hepatic Structures Using Cubic Hermite Elements
Attention for Chapter 15: Abdominal Images Non-rigid Registration Using Local-Affine Diffeomorphic Demons
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Chapter title
Abdominal Images Non-rigid Registration Using Local-Affine Diffeomorphic Demons
Chapter number 15
Book title
Abdominal Imaging. Computational and Clinical Applications
Published by
Springer, Berlin, Heidelberg, September 2011
DOI 10.1007/978-3-642-28557-8_15
Book ISBNs
978-3-64-228556-1, 978-3-64-228557-8
Authors

Moti Freiman, Stephan D. Voss, Simon Keith Warfield

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 14%
Other 1 14%
Student > Bachelor 1 14%
Student > Master 1 14%
Researcher 1 14%
Other 1 14%
Unknown 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Engineering 1 14%
Unknown 3 43%