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Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation
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Zepa Yang ,
Contributed equally to this work with: Zepa Yang, Juwhan Choi, Hwan Seok Yong
Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing
Affiliation Department of Radiology, Korea University Guro Hospital, Seoul, Republic of Korea
⨯ - Insung Choi,
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Juwhan Choi ,
Contributed equally to this work with: Zepa Yang, Juwhan Choi, Hwan Seok Yong
Roles Data curation, Investigation, Methodology, Validation
Affiliation Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, Republic of Korea
⨯ - Jongha Jung,
- Minyeong Ryu,
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Hwan Seok Yong
Contributed equally to this work with: Zepa Yang, Juwhan Choi, Hwan Seok Yong
Roles Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing – review & editing
* E-mail: yhwanseok@naver.com
Affiliation Department of Radiology, Korea University Guro Hospital, Seoul, Republic of Korea
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https://orcid.org/0000-0001-8089-7396
Deep learning-based pectoralis muscle volume segmentation method from chest computed tomography image using sagittal range detection and axial slice-based segmentation
- Zepa Yang,
- Insung Choi,
- Juwhan Choi,
- Jongha Jung,
- Minyeong Ryu,
- Hwan Seok Yong
- Published: September 5, 2023
- https://doi.org/10.1371/journal.pone.0290950