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Proceedings Paper

Automated detection of ureter abnormalities on multi-detector row CT urography
Author(s): Lubomir Hadjiiski; Berkman Sahiner; Elaine M. Caoili; Richard H. Cohan; Heang-Ping Chan
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Paper Abstract

We are developing a CAD system for automated detection of ureter abnormalities on multi-detector row CT urography, which potentially can assist radiologists in detecting ureter cancer. In the first stage of the CAD system, given an initial starting point, the ureter is tracked based on the CT values of the contrast-filled lumen. In the second stage, lesion candidates are detected using histogram and shape analysis to separate the abnormality from the background, which is the ureter filled with contrast material. A uniformity measure is designed to detect non-uniformity of the CT values within the ureter volume. If a ureter abnormality is present, the CT values uniformity will be distorted, resulting in a reduced uniformity measure. The smoothness of the ureter wall is also estimated using a shape measure. A rule-based system is used to combine the two measures. In this pilot study, a limited data set of 11 patients with biopsy-proven lesions was used. Nine patients had 12 ureter cancers and 6 benign lesions and the remaining two patients had 2 benign lesions. The average lesions size for the 12 cancers was 7.8mm (range: 2.1mm-9.5mm). The tracking program successfully tracked the ureters in 10 of the patients. Our system detected 75% (15/20) of the ureter lesions with 2.6 (28/11) false positives per patient. 83% (10/12) of the ureter cancers were detected. The preliminary results show that our detection system can track the ureter and detect ureter cancer of medium conspicuity and relatively small size.

Paper Details

Date Published: 10 March 2006
PDF: 7 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441W (10 March 2006); doi: 10.1117/12.654985
Show Author Affiliations
Lubomir Hadjiiski, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Elaine M. Caoili, Univ. of Michigan (United States)
Richard H. Cohan, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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