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Proceedings Paper

Electronic stool subtraction using quadratic regression, morphological operations, and distance transforms
Author(s): Michael Carston; Armando Manduca; C. Daniel Johnson
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Paper Abstract

CT colonography (CTC) is being extensively studied for its potential value in colon examinations, since it offers many advantages such as lower risk and less patient discomfort. However, CTC, like all other types of full structural colorectal examinations to date, requires complete bowel preparation. The inconvenience and discomfort associated with this preparation is an important obstacle to compliance with currently recommended colorectal screening guidelines. To maximize compliance, CTC would ideally be performed on an unprepared colon. However, in an unprepared colon residual stool and fluid can mimic soft tissue density and thus confound the identification of polyps. An alternative is to tag the stool with an opacifying agent so that it is brighter than soft tissue and thus easily recognized automatically and then reset to air values. However, such electronic stool subtraction in a totally unprepared colon is difficult to perform accurately for several reasons, including poorly labeled areas of stool, the need to accurately quantify partial volume effects, and noise. In this study the qualitative performance of a novel stool subtraction algorithm was assessed in unprepared CT colonography screening exams of 26 consecutive volunteers. Results showed that nearly all stool was removed in 62% of the cases, fold erosion was mild or nonexistent in 75% of the cases, and wall erosion was mild or non-existent in 100% of cases. Although further study and refinement of the stool subtraction process is required, CT colonography of the unprepared colon with electronic stool subtraction is feasible.

Paper Details

Date Published: 10 May 2007
PDF: 12 pages
Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65110W (10 May 2007); doi: 10.1117/12.713629
Show Author Affiliations
Michael Carston, Mayo Clinic College of Medicine (United States)
Armando Manduca, Mayo Clinic College of Medicine (United States)
C. Daniel Johnson, Mayo Clinic College of Medicine (United States)

Published in SPIE Proceedings Vol. 6511:
Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
Armando Manduca; Xiaoping P. Hu, Editor(s)

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