Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26400
Title: Location classification of lung nodules with optimized graph construction
Authors: Song, Y
Cai, W
Wang, Y
Feng, DD
Keywords: CT
Classification
Graph cut
Lung nodule
Issue Date: 2012
Publisher: IEEE
Source: 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2-5 May 2012, Barcelona, p. 1439-1442 How to cite?
Abstract: The locations of lung nodules relative to the other lung anatomical structures are important hints of malignant cancers. In this paper, we propose a fully automatic method to identify if a lung nodule is well-circumscribed, juxta-vascular, juxta-pleural or pleural tail in computed tomography (CT) images. First, we design an optimized graph model, introducing new global and region-based energy terms, to label each voxel as background or foreground in a single graph cut algorithm. Then, the texture features of a lung nodule are extracted based on the voxel labeling outputs, and its location information is inferred. We evaluate the proposed method on low-dose CT images, and demonstrate highly effective nodule classification results comparatively.
URI: http://hdl.handle.net/10397/26400
ISBN: 978-1-4577-1857-1
ISSN: 1945-7928
DOI: 10.1109/ISBI.2012.6235841
Appears in Collections:Conference Paper

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