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9 March 2011 Automated segmentation of pulmonary nodule depicted on CT images
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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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiantao Pu and Jun Tan "Automated segmentation of pulmonary nodule depicted on CT images", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79632Z (9 March 2011); https://doi.org/10.1117/12.878038
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