Validating Pareto optimal operation parameters of polyp detection algorithms for CT colonography

Jiang Li, Adam Huang, Nicholas Petrick, Jianhua Yao, Ronald M. Summers

研究成果: 書貢獻/報告類型會議論文篇章同行評審

4 引文 斯高帕斯(Scopus)


We evaluated a Pareto front-based multiobjective 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 an 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 multiobjective 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.

主出版物標題Medical Imaging 2007
主出版物子標題Computer-Aided Diagnosis
版本PART 2
出版狀態已出版 - 2007
事件Medical Imaging 2007: Computer-Aided Diagnosis - San Diego, CA, United States
持續時間: 20 2月 200722 2月 2007


名字Progress in Biomedical Optics and Imaging - Proceedings of SPIE
號碼PART 2


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國家/地區United States
城市San Diego, CA


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