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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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| 出版年: | Healthc Inform Res |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Korean Society of Medical Informatics
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5116543/ https://ncbi.nlm.nih.gov/pubmed/27895963 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4258/hir.2016.22.4.305 |
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