Evaluation of Semi-automatic Segmentation Methods for Persistent Ground Glass Nodules on Thin-Section CT Scans-Reference-Cited by-同舟云学术

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

Published:2016 Issue:4 Volume:22 Page:305
ISSN:2093-3681
Container-title:Healthcare Informatics Research
language:en
Short-container-title:Healthc Inform Res

Author:

Kim Young Jae¹²,Lee Seung Hyun²,Park Chang Min³,Kim Kwang Gi¹

Affiliation:

1. Biomedical Engineering Branch, Division of Precision Medicine and Cancer Informatics, Research Institute, National Cancer Center, Goyang, Korea.

2. Department of Plasma Bio Display, Kwangwoon University, Seoul, Korea.

3. Department of Radiology, Seoul National University Hospital, Seoul, Korea.

Publisher

The Korean Society of Medical Informatics

Subject

Health Information Management,Health Informatics,Biomedical Engineering

Link

http://synapse.koreamed.org/pdf/10.4258/hir.2016.22.4.305

Reference30 articles.

1. Cancer statistics, 2011

2. The Role and Significance of Biomarker for Plasma G-CSF in Patients with Primary Lung Cancer

3. Focal Ground-Glass Opacity Detected by Low-Dose Helical CT

4. The 2004 World Health Organization classification of lung tumors

5. Nodular Ground-Glass Opacity at Thin-Section CT: Histologic Correlation and Evaluation of Change at Follow-up

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