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Computer-aided diagnosis of Ground Glass Opacity Lung Nodules: Quantitative results in 248 patients

Institution:
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publication Date:
Nov-2015
Citation:
The Radiological Society of North America 101st Scientific Assembly and Annual Meeting, 2015 November, Chicago, IL, USA.
Appears in Collections:
RSNA
Sponsors:
P41 EB015898/EB/NIBIB NIH HHS/United States
P41 RR019703/RR/NCRR NIH HHS/United States
Generated Citation:
Li M., Narayan V., Barile M.F., Gill R., Bueno R., Tempany C.M., Jayender J. Computer-aided diagnosis of Ground Glass Opacity Lung Nodules: Quantitative results in 248 patients. The Radiological Society of North America 101st Scientific Assembly and Annual Meeting, 2015 November, Chicago, IL, USA.
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Lung adenocarcinoma’s new classification is based on histological criteria. There is a need to develop image-based classification of GGNs into AAH, AIS, MIA and IAC. We propose a Support Vector Machine algorithm with input as tumor heterogeneity metrics to predict the lesion type on CT images.