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Proceedings Paper

Automatic colonic fold segmentation for computed tomography colonography
Author(s): Hongbin Zhu; Matthew Barish; Lihong Li; Bowen Song; Donald Harrington; Perry Pickhardt M.D.; Zhengrong Liang
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Paper Abstract

Human colon has complex structures mostly because of the haustral folds. Haustral folds are thin flat protrusions on the colon wall, which inherently attached on the colon wall. These structures may complicate the shape analysis for computer-aided detection of colonic polyps (CADpolyp); however, they can serve as solid reference during image interpretation in computed tomographic colonography (CTC). Therefore, in this study, based on a clear model of the haustral fold boundaries, we employ level set method to automatically segment the fold surfaces. We believe the segmented folds have the potential to significantly benefit various post-procedures in CTC, e.g., supine-prone registration, synchronized image interpretation, automatic polyp matching, CADpolyp, teniae coli extraction, etc. For the first time, with assistance from physician experts, we established the ground truth of haustral fold boundaries of 15 real patient data from two medical centers, based on which we evaluated our algorithm. The results demonstrated that about 92.7% of the folds are successfully detected. Furthermore, we explored the segmented area ratio (SAR), i.e., the ratio between the areas of the intersection and the union of the expert-drawn and the automatically-segmented folds, to measure the accuracy of the segmentation algorithm. The averaged result of SAR=86.2% shows a good match between the ground truth and our segmentation results.

Paper Details

Date Published: 23 February 2012
PDF: 7 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83150X (23 February 2012); doi: 10.1117/12.911336
Show Author Affiliations
Hongbin Zhu, Stony Brook Univ. (United States)
Matthew Barish, Stony Brook Univ. (United States)
Lihong Li, College of Staten Island (United States)
Bowen Song, Stony Brook Univ. (United States)
Donald Harrington, Stony Brook Univ. (United States)
Perry Pickhardt M.D., Univ. of Wisconsin-Madison (United States)
Zhengrong Liang, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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