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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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공학
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JoVE 신문 공학
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

2,305 Views

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04:48 min

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November 30, 2022

DOI:

10.3791/64500-v

DOI:
10.3791/64500-v

•

04:48 min
November 30, 2022

•

7 Views
, , ,
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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An object segmentation protocol for orbital computed tomography (CT) images is introduced. The methods of labeling the ground truth of orbital structures by using super-resolution, extracting the volume of interest from CT images, and modeling multi-label segmentation using 2D sequential U-Net for orbital CT images are explained for supervised learning.

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Cite this Article

Chung, Y. W., Kang, D. G., Lee, Y. O., Cho, W. Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography. J. Vis. Exp. (189), e64500, doi:10.3791/64500 (2022).

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