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Proceedings Paper

Automatic colonic polyp detection using multi-objective evolutionary techniques
Author(s): Jiang Li; Adam Huang; Jianhua Yao; Ingmar Bitter; Nicholas Petrick; Ronald M. Summers; Perry J. Pickhardt; J. Richard Choi
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Paper Abstract

Colonic polyps appear like elliptical protrusions on the inner wall of the colon. Curvature based features for colonic polyp detection have proved to be successful in several computer-aided diagnostic CT colonography (CTC) systems. Some simple thresholds are set for those features for creating initial polyp candidates, sophisticated classification scheme are then applied on these polyp candidates to reduce false positives. There are two objective functions, the number of missed polyps and false positive rate, that need to be minimized when setting those thresholds. These two objectives conflict and it is usually difficult to optimize them both by a gradient search. In this paper, we utilized a multiobjective evolutionary method, the Strength Pareto Evolutionary Algorithm (SPEA2), to optimize those thresholds. SPEA2 incorporates the concept of Pareto dominance and applies genetic techniques to evolve individual solutions to the Pareto front. The SPEA2 algorithm was applied to colon CT images from 27 patients each having a prone and a supine scan. There are 40 colonoscopically confirmed polyps resulting in 72 positive detections in CTC reading. The results obtained by SPEA2 were compared with those obtained by our old system, where an appropriate value was set for each of those thresholds by a histogram examination method. If we keep the sensitivity the same as that of our old system, the SPEA2 algorithm reduced false positive rate by 76.4% from average false positive 55.6 to 13.3 per data set. If the false positive rate is kept the same for both systems, SPEA2 increased the sensitivity by 13.1% from 53 to 61 among 72 ground truth detections.

Paper Details

Date Published: 15 March 2006
PDF: 9 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61445E (15 March 2006); doi: 10.1117/12.653546
Show Author Affiliations
Jiang Li, National Institutes of Health (United States)
Adam Huang, National Institutes of Health (United States)
Jianhua Yao, National Institutes of Health (United States)
Ingmar Bitter, National Institutes of Health (United States)
Nicholas Petrick, U.S. Food and Drug Administration (United States)
Ronald M. Summers, National Institutes of Health (United States)
Perry J. Pickhardt, Uniformed Services, Univ. of the Health Sciences (United States)
National Naval Medical Ctr. (United States)
J. Richard Choi, Uniformed Services, Univ. of the Health Sciences (United States)
Walter Reed Army Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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