Name
Abstract | ||
|---|---|---|
Due to its importance and possible applications in visualization, tumor detection and preoperative planning, automatic small bowel segmentation is essential for computer-aided diagnosis of small bowel pathology. However, segmenting the small bowel directly on computed tomography (CT) scans is very difficult because of the low image contrast on CT scans and high tortuosity of the small bowel and its close proximity to other abdominal organs. Motivated by the intensity characteristics of abdominal CT images, the anatomic relationship between the mesenteric vasculature and the small bowel, and potential usefulness of the mesenteric vasculature for establishing the path of the small bowel, we propose a novel mesenteric vasculature map-guided method for small bowel segmentation on high-resolution CT angiography scans. The major mesenteric arteries are first segmented using a vessel tracing method based on multi-linear subspace vessel model and Bayesian inference. Second, multi-view, multi-scale vesselness enhancement filters are used to segment small vessels, and vessels directly or indirectly connecting to the superior mesenteric artery are classified as mesenteric vessels. Third, a mesenteric vasculature map is built by linking vessel bifurcation points, and the small bowel is segmented by employing the mesenteric vessel map and fuzzy connectness. The method was evaluated on 11 abdominal CT scans of patients suspected of having carcinoid tumors with manually labeled reference standard. The result, 82.5% volume overlap accuracy compared with the reference standard, shows it is feasible to segment the small bowel on CT scans using the mesenteric vasculature as a roadmap. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TMI.2013.2271487 | IEEE Trans. Med. Imaging |
Keywords | DocType | Volume |
mesenteric arteries,vessel bifurcation points,fuzzy set theory,diagnostic radiography,computerised tomography,manually labeled reference standard,vessel tracing,inference mechanisms,blood vessels,image segmentation,computed tomography,vessel tracing method,mesenteric vasculature-guided small bowel segmentation,bayesian inference,high-resolution ct angiography scans,abdominal ct images,fuzzy connectness,multiscale vesselness enhancement filters,bayes methods,multilinear subspace vessel model,carcinoid tumors,filtering theory,tumours,vesselness enhancement,preoperative planning,small bowel pathology,small bowel segmentation,computer-aided diagnosis,medical image processing,3d ct,tumor detection | Journal | 32 |
Issue | ISSN | Citations |
11 | 1558-254X | 7 |
PageRank | References | Authors |
0.53 | 16 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weidong Zhang | 1 | 19 | 2.52 |
| Jiamin Liu | 2 | 319 | 24.10 |
| Jianhua Yao | 3 | 1135 | 110.49 |
| Adeline Louie | 4 | 12 | 1.37 |
| Tan Nguyen | 5 | 61 | 5.22 |
| Stephen Wank | 6 | 11 | 1.02 |
| Wieslaw L. Nowinski | 7 | 337 | 47.85 |
| Ronald M Summers | 8 | 35 | 4.56 |