AISLE: an automatic volumetric segmentation method for the study of lung allometry
Ren, H.; Kazanzides, P.
Studies in Health Technology and Informatics 163: 476-478
2011
ISSN/ISBN: 0926-9630 PMID: 21335842 Document Number: 652493
We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.