Abstract
Most current computer-aided detection (CAD) algorithms for the fully automatic detection of colonic polyps from 3D CT data suffer from high false positive rates. We developed and evaluated a post-processing algorithm to decrease the false positive rate of such a method. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through 3D CT data by quantifying the change in location of the edges in 2D plane. It uses a classifier for identification based on the Mahalanobis distance. The new method increased the ROC curve area from 0.89 to 0.98 (an increase from 34.5% to 85.0% in specificity for 100% sensitivity) in a population of 8 patients.
Original language | English (US) |
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Pages (from-to) | 2774-2777 |
Number of pages | 4 |
Journal | Annual Reports of the Research Reactor Institute, Kyoto University |
Volume | 3 |
State | Published - 2001 |
Externally published | Yes |
Event | 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey Duration: Oct 25 2001 → Oct 28 2001 |
Keywords
- CAD
- Computed tomographic colonography
- Optical flow fields
- Polyp detection
- Virtual colonoscopy
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Mechanical Engineering