Document Type

Conference Paper

Publication Date

2007

DOI

10.1117/12.707965

Publication Title

Medical Imaging 2007: Computer-Aided Diagnosis, Proceedings of SPIE Vol. 6514

Volume

6514

Pages

65142G

Conference Name

Medical Imaging 2007: Computer-Aided Diagnosis, February 17-22, 2007

Abstract

We evaluated a Pareto front-based multi-objective evolutionary algorithm for optimizing our CT colonography (CTC) computer-aided detection (CAD) system. The system identifies colonic polyps based on curvature and volumetric based features, where a set of thresholds for these features was optimized by the evolutionary algorithm. We utilized a two-fold cross-validation (CV) method to test if the optimized thresholds can be generalized to new data sets. We performed the CV method on 133 patients; each patient had a prone and a supine scan. There were 103 colonoscopically confirmed polyps resulting in 188 positive detections in CTC reading from either the prone or the supine scan or both. In the two-fold CV, we randomly divided the 133 patients into two cohorts. Each cohort was used to obtain the Pareto front by a multi-objective genetic algorithm, where a set of optimized thresholds was applied on the test cohort to get test results. This process was repeated twice so that each cohort was used in the training and testing process once. We averaged the two training Pareto fronts as our final training Pareto front and averaged the test results from the two runs in the CV as our final test results. Our experiments demonstrated that the averaged testing results were close to the mean Pareto front determined from the training process. We conclude that the Pareto front-based algorithm appears to be generalizable to new test data.

Rights

© 2007 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., Petrick, N., Yao, J., & Summers, R. (2007). Validating Pareto optimal operation parameters of polyp detection algorithms for CT colonography. In M.L. Giger & N. Karssemeijer (Eds.), Medical Imaging 2007: Computer-Aided Diagnosis, Proceedings of SPIE Vol. 6514 (65142G). SPIE of Bellingham, WA. https://doi.org/10.1117/12.707965

ORCID

0000-0003-0091-6986 (Li)

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