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Automated Analysis of Quantitative Image Biomarkers from Low-Dose Chest CT Scans

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개인저자Liu, Shuang.
단체저자명Cornell University. Electrical & Computer Engineering.
서명/저자사항Automated Analysis of Quantitative Image Biomarkers from Low-Dose Chest CT Scans.
발행사항[S.l.] : Cornell University., 2018
발행사항Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항170 p.
소장본 주기School code: 0058.
ISBN9780438343542
일반주기 Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Anthony P. Reeves.
요약A quantitative imaging biomarker is a quantitatively measured characteristic derived from medical images, which serves as cost-effective and noninvasive tools for patient health assessment, including diagnosis and periodic screening of disease,
요약This dissertation presents an automated framework for quantitative image biomarker measurement and evaluation from the low-dose chest CT (LDCT) scans that are acquired during the annual lung cancer screening. Four categories of quantitative imag
요약In conclusion, with the recent large-scale implementation of annual lung cancer screening in the US using LDCT, great potential emerges for the concurrent extraction of quantitative image biomarkers from different regions in the chest, which are
일반주제명Computer engineering.
Computer science.
Electrical engineering.
Artificial intelligence.
Medical imaging.
언어영어
기본자료 저록Dissertation Abstracts International80-01B(E).
Dissertation Abstract International
대출바로가기http://www.riss.kr/pdu/ddodLink.do?id=T15000052

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