Dawn of the Visible Monkey: Segmentation of the Rhesus Monkey for 2D and 3D Applications
Journal of Korean Medical Science
; : e100-2020.
Article
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| WPRIM
| ID: wpr-831486
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WPRO
ABSTRACT
Background@#To properly utilize the sectioned images in a Visible Monkey dataset, it is essential to segment the images into distinct structures. This segmentation allows the sectioned images to be compiled into two-dimensional or three-dimensional software packages to facilitate anatomy and radiology education, and allows them to be used in experiments involving electromagnetic radiation. The purpose of the present study was to demonstrate the potential of the sectioned images using the segmented images. @*Methods@#Using sectioned images of a monkey's entire body, 167 structures were segmented using Adobe Photoshop. The segmented images and sectioned images were packaged into the browsing software. Surface models were made from the segmented images using Mimics. Volume models were made from the sectioned images and segmented images using MRIcroGL. @*Results@#In total, 839 segmented images of 167 structures in the entire body of a monkey were produced at 0.5-mm intervals (pixel size, 0.024 mm; resolution, 8,688 × 5,792; color depth, 24-bit color; BMP format). Using the browsing software, the sectioned images and segmented images were able to be observed continuously and magnified along with the names of the structures. The surface models of PDF file were able to be handled freely using Adobe Reader. In the surface models, the space information of all segmented structures was able to be identified using Sim4Life. On MRIcroGL, the volume model was able to be browsed and sectioned at any angle with real color. @*Conclusion@#Browsing software, surface models, and volume models are able to be produced based on the segmentation of the sectioned images. These will be helpful for students and researchers studying monkey anatomy and radiology, as well as for biophysicists examining the effects of electromagnetic radiation.
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WPRIM
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Texte intégral:
Journal of Korean Medical Science
Année:
2020
Type:
Article