Evaluation of Semi-automatic Segmentation Methods for Persistent Ground Glass Nodules on Thin-Section CT Scans

Evaluation of Semi-automatic Segmentation Methods for Persistent Ground Glass Nodules on Thin-Section CT Scans

ObjectivesThis work was a comparative study that aimed to find a proper method for accurately segmenting persistent ground glass nodules (GGN) in thin-section computed tomography (CT) images after detecting them.MethodsTo do this, we first applied five types of semi-automatic segmentation methods (i...

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Bibliographic Details
Main Authors:	Young Jae Kim, Seung Hyun Lee, Chang Min Park, Kwang Gi Kim
Format:	Article
Language:	English
Published:	The Korean Society of Medical Informatics 2016-10-01
Series:	Healthcare Informatics Research
Subjects:	lung computer-assisted image processing solitary pulmonary nodule computer-assisted diagnosis x-ray computed tomography scanners
Online Access:	http://e-hir.org/upload/pdf/hir-22-305.pdf

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