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Lung segmentation and tumor detection from CT thorax volumes of FDG PET-CT scans by template registration and incorporation of functional information

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5 Author(s)
Cherry Ballangan ; Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Australia ; Xiuying Wang ; Dagan Feng ; Stefan Eberl
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Automatic segmentation and detection of lungs and tumors in FDG PET-CT images is potentially beneficial in the diagnosis and staging of patients with non-small cell lung cancer (NSCLC). However, simultaneous lung segmentation and tumor detection is not a trivial task, particularly due to noise in the datasets, proximity of the lung lesion to the mediastinum and chest wall in certain instances, and disease involvement of non-enlarged lymph nodes.

Published in:

2008 IEEE Nuclear Science Symposium Conference Record

Date of Conference:

19-25 Oct. 2008