Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1117/12.878038 | Proceedings of SPIE |
Keywords | DocType | Volume |
Lung Nodule,Computer-aided Detection (CAD),Segmentation,Shape analysis | Conference | 7963 |
ISSN | Citations | PageRank |
0277-786X | 0 | 0.34 |
References | Authors | |
8 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiantao Pu | 1 | 277 | 23.12 |
| Jun Tan | 2 | 3 | 1.68 |