Paper
10 May 2007 Electronic stool subtraction using quadratic regression, morphological operations, and distance transforms
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Carston, Armando Manduca, and C. Daniel Johnson "Electronic stool subtraction using quadratic regression, morphological operations, and distance transforms", Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65110W (10 May 2007); https://doi.org/10.1117/12.713629
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Cited by 7 scholarly publications and 1 patent.
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KEYWORDS
Tissues

Colon

Virtual colonoscopy

Transform theory

Picosecond phenomena

Colorectal cancer

Algorithm development

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