Improving polyp detection algorithms for CT colonography: Pareto front approach

Authors:
Adam Huang;Jiang Li;Ronald M. Summers;Nicholas Petrick;Amy K. Hara
Affiliations:
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, United States and Research Cente ...;Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, United States and Department of ...;Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, United States;National Institute of Biomedical Imaging and Bioengineering (NIBIB)/Center for Devices and Radiological Health Laboratory for the Assessment of Medical Imaging Systems, US Food and Drug Administra ...;Diagnostic Radiology, Mayo Clinic in Scottsdale, Scottsdale, AZ 85259, United States
Venue:
Pattern Recognition Letters
Year:
2010

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Abstract

We investigated a Pareto front approach to improve polyp detection algorithms for CT colonography (CTC). A dataset of 56 CTC colon surfaces with 87 proven positive detections of 53 polyps sized 4-60mm was used to evaluate the performance of a one-step and a two-step curvature-based region growing algorithm. The algorithmic performance was statistically evaluated and compared based on the Pareto optimal solutions from 20 experiments by evolutionary algorithms. The false positive rate was lower (p