title: Segmentation of juxtapleural pulmonary nodules using a robust surface estimate.
abstract: An algorithm was developed to segment solid pulmonary nodules attached to the chest wall in computed tomography scans. The pleural surface was estimated and used to segment the nodule from the chest wall. To estimate the surface, a robust approach was used to identify points that lie on the pleural surface but not on the nodule. A 3D surface was estimated from the identified surface points. The segmentation performance of the algorithm was evaluated on a database of 150 solid juxtapleural pulmonary nodules. Segmented images were rated on a scale of 1 to 4 based on visual inspection, with 3 and 4 considered acceptable. This algorithm offers a large improvement in the success rate of juxtapleural nodule segmentation, successfully segmenting 98.0% of nodules compared to 81.3% for a previously published plane-fitting algorithm, which will provide for the development of more robust automated nodule measurement methods.
authors: School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, USA.
authors: Artit C
authors: AC
authors: Jirapatnakul
authors: Yury D
authors: YD
authors: Mulman
authors: Anthony P
authors: AP
authors: Reeves
authors: David F
authors: DF
authors: Yankelevitz
authors: Claudia I
authors: CI
authors: Henschke