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

OBJECTIVES: This 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. METHODS: To do this, we first applied five types of semi-automatic segmentation metho...

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Detalles Bibliográficos
Autores principales: Kim, Young Jae, Lee, Seung Hyun, Park, Chang Min, Kim, Kwang Gi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2016
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116543/
https://www.ncbi.nlm.nih.gov/pubmed/27895963
http://dx.doi.org/10.4258/hir.2016.22.4.305

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116543/
https://www.ncbi.nlm.nih.gov/pubmed/27895963
http://dx.doi.org/10.4258/hir.2016.22.4.305

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