Paper
2 May 2003 Polyp segmentation method for CT colonography computer-aided detection
Anna K. Jerebko, Sheldon Teerlink, Marek Franaszek, Ronald M. Summers
Author Affiliations +
Abstract
We have developed a new method employing the Canny edge detector and Radon transformation to segment images of polyp candidates for CT colonography (CTC) computer aided polyp detection and obtain features useful for distinguishing true polyps from false positive detections. The technique is applied to two-dimensional subimages of polyp candidates selected using various 3-D shape and curvature characteristics. We detect boundaries using the Canny operator. The baseline of the colon wall is detected by applying the Radon transform to the edge image and locating the strongest peak in the resulting transform matrix. The following features are calculated and used to classify detections as true positives (TP) and false positives (FP): polyp boundary length, polyp base length, polyp internal area, average intensity, polyp height, and inscribed circle radius. The segmentation technique was applied to a data set of 15 polyps larger than 3 mm and 617 false positives taken from 80 CTC studies (supine and prone screening of 40 patients). The sensitivity was 100% (15 of 15). 58% of the FP's were eliminated leaving an average of 3 false positives per study. Our method is able to segment polyps and quantitatively measure polyp features independently of orientation and shape.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anna K. Jerebko, Sheldon Teerlink, Marek Franaszek, and Ronald M. Summers "Polyp segmentation method for CT colonography computer-aided detection", Proc. SPIE 5031, Medical Imaging 2003: Physiology and Function: Methods, Systems, and Applications, (2 May 2003); https://doi.org/10.1117/12.480696
Lens.org Logo
CITATIONS
Cited by 17 scholarly publications and 3 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Colon

Image segmentation

Sensors

Virtual colonoscopy

Image processing

Computer aided diagnosis and therapy

Tissues

Back to Top