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Proceedings Paper

Probabilistic method for virtual colonoscopy cleansing
Author(s): Iwo Serlie; Roel Truyen; Geert de Vries; Frits H. Post; Frans M. Vos
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Paper Abstract

Currently, virtual colonoscopy examinations require extensive bowel preparation because residual materials can occlude lesions or can be misinterpreted as polyps. Our goal is to investigate a probabilistic method to segment contrast enhanced residual materials and remove them from the rendering. The region around a sample position is modeled to contain mixtures of air, tissue and tagged intraluminal remains. For each image sample a probability vector is calculated expressing the probability that the materials of interest are present. A probability space is defined using the probabilities for pure materials as base vectors. Mixture vectors are constructed at 45-degree angles between the pure material vectors. The probability vectors are compared to the base vectors and the mixture vectors to classify them into material mixtures. Consider the layer between air and tagged fluid. Image intensities are similar to tissue. The scale at which the Gaussian averaged probability is calculated is increased until convergence: two successive scales result in the same classification. The Bayesian classification method shows good results with relatively large objects. However, edges of small or thin objects are likely to be misclassified: a too large environment is needed for convergence.

Paper Details

Date Published: 2 May 2003
PDF: 8 pages
Proc. SPIE 5031, Medical Imaging 2003: Physiology and Function: Methods, Systems, and Applications, (2 May 2003); doi: 10.1117/12.480403
Show Author Affiliations
Iwo Serlie, Delft Univ. of Technology (Netherlands)
Roel Truyen, Philips Medical Systems Nederlands BV (Netherlands)
Geert de Vries, Delft Univ. of Technology (Netherlands)
Frits H. Post, Delft Univ. of Technology (Netherlands)
Frans M. Vos, Delft Univ. of Technology (Netherlands)
Academic Medical Ctr. of Amsterdam (Netherlands)

Published in SPIE Proceedings Vol. 5031:
Medical Imaging 2003: Physiology and Function: Methods, Systems, and Applications
Anne V. Clough; Amir A. Amini, Editor(s)

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