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Anvendelse av dyp læringsbasert medisinsk bildesegmentering via orbital computertomografi
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Anvendelse av dyp læringsbasert medisinsk bildesegmentering via orbital computertomografi

Article DOI: 10.3791/64500-v • 04:48 min • November 30th, 2022
November 30th, 2022 •
1,2, 3, 4, 1,5
1College of Medicine, The Catholic University of Korea, 2Department of Ophthalmology, St. Vincent’s Hospital, 3Yeoncheon Public Medical Center, 4Department of Industrial and Data Engineering, Hongik University, 5Department of Ophthalmology, Uijeongbu St. Mary’s Hospital

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En objektsegmenteringsprotokoll for orbital computertomografi (CT) bilder blir introdusert. Metodene for å merke bakken sannheten av orbitale strukturer ved hjelp av superoppløsning, trekke ut volumet av interesse fra CT-bilder, og modellering multi-label segmentering ved hjelp av 2D sekvensielle U-Net for orbital CT bilder er forklart for overvåket læring.

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