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Proceedings Paper

Automated segmentation of pulmonary nodule depicted on CT images
Author(s): Jiantao Pu; Jun Tan
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Paper Abstract

In this study, an efficient computational geometry approach is introduced to segment pulmonary nodules. The basic idea is to estimate the three-dimensional surface of a nodule in question by analyzing the shape characteristics of its surrounding tissues in geometric space. Given a seed point or a specific location where a suspicious nodule may be, three steps are involved in this approach. First, a sub-volume centered at this seed point is extracted and the contained anatomy structures are modeled in the form of a triangle mesh surface. Second, a "visibility" test combined with a shape classification algorithm based on principal curvature analysis removes surfaces determined not to belong to nodule boundaries by specific rules. This step results in a partial surface of a nodule boundary. Third, an interpolation / extrapolation based shape reconstruction procedure is used to estimate a complete nodule surface by representing the partial surface as an implicit function. The preliminary experiments on 158 annotated CT examinations demonstrated that this scheme could achieve a reasonable performance in nodule segmentation.

Paper Details

Date Published: 9 March 2011
PDF: 7 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79632Z (9 March 2011); doi: 10.1117/12.878038
Show Author Affiliations
Jiantao Pu, Univ. of Pittsburgh Medical Ctr. (United States)
Jun Tan, Univ. of Pittsburgh Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers M.D.; Bram van Ginneken, Editor(s)

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