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Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities

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Cover of 'Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities'

Table of Contents

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    Book Overview
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    Chapter 1 Electronic Cleansing in CT Colonography: Past, Present, and Future
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    Chapter 2 Improved Curvature Estimation for Shape Analysis in Computer-Aided Detection of Colonic Polyps
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    Chapter 3 Characterizing Colonic Detections in CT Colonography Using Curvature-Based Feature Descriptor and Bag-of-Words Model
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    Chapter 4 Haustral Fold Segmentation of CT Colonography Using Ridge Line Detection
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    Chapter 5 Recent Advances in Reduction of False Positives in Computerized Detection of Polyps in CT Colonography
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    Chapter 6 Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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    Chapter 7 False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography: A Massive-Training Support Vector Regression Approach
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    Chapter 8 Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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    Chapter 9 Estimation of Necrosis Volumes in Focal Liver Lesions Based on Multi-phase Hepatic CT Images
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    Chapter 10 Detection of the Invasion of Bladder Tumor into Adjacent Wall Based on Textural Features Extracted from MRI Images
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    Chapter 11 Detecting Bladder Abnormalities Based on Inter-layer Intensity Curve for Virtual Cystoscopy
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    Chapter 12 Computer-Assisted Diagnosis for Quantitative Image-Based Analysis of Crohn’s Disease in CT Enterography
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    Chapter 13 Computer-Aided Detection of Small Bowel Strictures for Emergency Radiology in CT Enterography
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    Chapter 14 Teniae Coli Extraction in Human Colon for Computed Tomographic Colonography Images
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    Chapter 15 Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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    Chapter 16 Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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    Chapter 17 Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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    Chapter 18 Synchronized Display of Virtual Colonoscopic Views in Supine and Prone CT Images
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    Chapter 19 Colorectal Polyp Segmentation Based on Geodesic Active Contours with a Shape-Prior Model
Attention for Chapter 6: Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
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Chapter title
Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
Chapter number 6
Book title
Virtual Colonoscopy and Abdominal Imaging. Computational Challenges and Clinical Opportunities
Published in
Lecture notes in computer science, January 2011
DOI 10.1007/978-3-642-25719-3_6
Book ISBNs
978-3-64-225718-6, 978-3-64-225719-3
Authors

Ye, X., Xujiong Ye, Gareth Beddoe, Greg Slabaugh

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Professor > Associate Professor 1 33%
Readers by discipline Count As %
Medicine and Dentistry 3 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2015.
All research outputs
#17,803,516
of 22,870,727 outputs
Outputs from Lecture notes in computer science
#5,932
of 8,127 outputs
Outputs of similar age
#159,114
of 180,931 outputs
Outputs of similar age from Lecture notes in computer science
#223
of 317 outputs
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So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.