Paper Info
Title
Part-based local shape models for colon polyp detection.
Abstract
This paper presents a model-based technique for lesion detection in colon CT scans that uses analytical shape models to map the local shape curvature at individual voxels to anatomical labels. Local intensity profiles and curvature information have been previously used for discriminating between simple geometric shapes such as spherical and cylindrical structures. This paper introduces novel analytical shape models for colon-specific anatomy, viz. folds and polyps, built by combining parts with simpler geometric shapes. The models better approximate the actual shapes of relevant anatomical structures while allowing the application of model-based analysis on the simpler model parts. All parameters are derived from the analytical models, resulting in a simple voxel labeling scheme for classifying individual voxels in a CT volume. The algorithm's performance is evaluated against expert-determined ground truth on a database of 42 scans and performance is quantified by free-response receiver-operator curves.
Year
DOI
Venue
2006
10.1007/11866763_59
MICCAI (2)
Keywords
Field
DocType
ct volume,analytical model,local shape curvature,simple geometric shape,colon polyp detection,anatomical label,analytical shape model,part-based local shape model,individual voxels,simpler geometric shape,novel analytical shape model,actual shape,ct scan,receiver operator curve,ground truth
Voxel,Computer vision,Curvature,Pattern recognition,Computer science,Principal curvature,Ground truth,Medical image computing,Artificial intelligence,Geometric shape,Virtual colonoscopy,Shape analysis (digital geometry)
Conference
Volume
Issue
ISSN
9
Pt 2
0302-9743
ISBN
Citations 
PageRank 
3-540-44727-X
5
0.50
References 
Authors
6
8
Name
Order
Citations
PageRank
Rahul Bhotika114217.94
Paulo R. S. Mendonça261050.38
Saad A. Sirohey3896.97
Wesley D. Turner4253.37
Ying-Lin Lee5151.45
Julie M McCoy650.50
Rebecca E B Brown750.50
James V. Miller820851.13