Document Type
Conference Paper
Publication Date
2006
DOI
10.1117/12.653546
Publication Title
Medical Imaging 2006: Image Processing, Proceedings of SPIE Volume 6144
Volume
6144
Pages
61445E
Conference Name
Medical Imaging 2006: Image Processing, February 11-16, 2006, San Diego, California
Abstract
Colonie polyps appear like elliptical protrusions on the inner wall of the colon. Curvature based features for colonie 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),1 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.
Rights
Copyright 2006 Society of Photo‑Optical Instrumentation Engineers (SPIE).
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
Original Publication Citation
Li, J., Huang, A., Yao, J., Bitter, I., Patrick, N., Summers, R. M., Pickhardt, P. J., & Cho, J. R. (2006) Automatic colonic polyp detection using multiobjective evolutionary techniques. In J.M. Reinhardt & J.P.W. Pluim (Eds.), Medical Imaging 2006: Image Processing, Proceedings of SPIE Volume 6144 (61445E). SPIE. https://doi.org/10.1117/12.653546
Repository Citation
Li, Jiang; Huang, Adam; Yao, Jianhua; Bitter, Ingmar; Petrick, Nicholas; Summers, Ronald M.; Pickhardt, Perry J.; and Choi, J. Richard, "Automatic Colonic Polyp Detection Using Multiobjective Evolutionary Techniques" (2006). Electrical & Computer Engineering Faculty Publications. 380.
https://digitalcommons.odu.edu/ece_fac_pubs/380
ORCID
0000-0003-0091-6986 (Li)
Included in
Diagnosis Commons, Digestive System Commons, Radiology Commons