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Proceedings Paper

Volumetric detection of flat lesions for minimal-preparation dual-energy CT colonography
Author(s): Janne J. Näppi; Se Hyung Kim; Hiroyuki Yoshida
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Paper Abstract

Computer-aided detection (CAD) systems for computed tomographic colonography (CTC) tend to miss many flat lesions. We developed a volumetric method for automated detection of lesions with dual-energy CTC (DECTC). The target region for the detection is defined in terms of a distance transform of the colonic lumen. To detect lesions, volumetric shape features are calculated at the image scale defined by the thickness of the target region. False-positive (FP) detections are reduced by use of a random-forest classifier based on shape, texture, and dual-energy features of the detected lesion candidates. For pilot evaluation, 37 patients were examined by use of DE-CTC with a reduced one-day bowel preparation. The CAD scheme was trained with the DE-CTC data of 12 patients, and it was tested with the DE-CTC data of 25 patients. The detection sensitivity was assessed at multiple thicknesses of the target region. There were 39 lesions ≥6 mm in 15 patients, including 8 flat lesions ≥10 mm. The thickness of the target region had a statistically significant effect on the detection sensitivity. At the optimal thickness of the target region, the per-lesion and per-patient sensitivities for flat lesions were 100% at a median of 4 FPs per patient.

Paper Details

Date Published: 28 February 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86702E (28 February 2013); doi: 10.1117/12.2008127
Show Author Affiliations
Janne J. Näppi, Massachusetts General Hospital (United States)
Harvard Medical School (United States)
Se Hyung Kim, Seoul National Univ. Hospital (Korea, Republic of)
Hiroyuki Yoshida, Massachusetts General Hospital (United States)
Harvard Medical School (United States)

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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