Paper Info
Title
Thin Layer Tissue Classification For Electronic Cleansing Of Ct Colonography Data
Abstract
CT colonography (CTC) is a rapidly evolving technique to screen for colorectal polyps. Fecal residue may occlude or, reversely, mimic polyps. Electronic cleansing aims at removing contrast-enhanced fecal residue from the image. However thin layers of soft tissue (the colon wall or a fold) or residue are easily misclassified by current electronic cleansing methods, thereby causing holes in the colon wall or other artefacts that hamper visualization and automated detection. We present a thin layer model to detect and characterize such layers to support electronic cleansing. It is demonstrated that the model sustains robust estimation of the location and thickness of such a layer Such thicknesses of thin layers were measured in real data sets. A lower bound on the thickness of such layers exists and was found to be 1.0 mm for our data.
Year
DOI
Venue
2008
10.1109/ICPR.2008.4760993
19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6
Keywords
Field
DocType
ct colonography,segmentation,electronic cleansing,tissue classificat ion,current transformers,computed tomography,lower bound,image classification,colon cancer,robust estimator
Biomedical engineering,Pattern recognition,Computer science,Artificial intelligence,Computed tomography,Thin layers,Colon wall
Conference
ISSN
Citations 
PageRank 
1051-4651
0
0.34
References 
Authors
7
5
Name
Order
Citations
PageRank
Vincent Frans van Ravesteijn1705.94
Frans M. Vos213318.49
Iwo Serlie31218.81
Roel Truyen421819.37
Lucas J. van Vliet5842113.16