@inproceedings{d29dd1b64d90458da66aad8d35dc6a95,
title = "Automated segmentation of pulmonary nodule depicted on CT images",
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.",
keywords = "Computer-aided Detection (CAD), Lung Nodule, Segmentation, Shape analysis",
author = "Jiantao Pu and Jun Tan",
year = "2011",
doi = "10.1117/12.878038",
language = "English (US)",
isbn = "9780819485052",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2011",
note = "Medical Imaging 2011: Computer-Aided Diagnosis ; Conference date: 15-02-2011 Through 17-02-2011",
}