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KMID : 1150820210340030057
Anatomy & Biological Anthropology
2021 Volume.34 No. 3 p.57 ~ p.65
Automated Techniques for the Sectioned Images of Visible Korean
Kim Chung-Yoh

Park Jin-Seo
Abstract
The sectioned images of Visible Korean Project can display the structures of entire body in detail by virtue of the real color and high resolution. To utilize the sectioned images for various purposes, automatic image processing should be done. However, the automation for the sectioned images could not be easily done because of real color and high resolution of the images. This study aimed to introduce automatic techniques for image processing of the sectioned images to help researchers save working times for this processing. The automatic techniques for the sectioned images were developed using commercial software such as Adobe Photoshop and Matlab and non-commercial software such as MRIcroGL and FMRIB Software Library. Also, we developed the self-developed software by C++ and JAVA script for the automatic techniques because some procedures unable to be processed using the software. By using the automatic techniques, the segmented images of some structures were made automatically from the sectioned images. From the sectioned images and the segmented images, the surface models and the volume models were produced automatically. To display both the sectioned images and segmented images, browsing software was used. To display the surface models and the volume model, Adobe Reader and MRIcroGL were used. By using the automaitc techniques, times and efforts for image processing of the sectioned images could be saved. However, since the automatic techniques could not produce complete results by itself, manual work should be done together in some procedures. To produce best results from the sectioned images, it was important to use the automation and the manual works in balance. In future studies, additional automatic techniques will be devised to reduce manual work for efficiency.
KEYWORD
Cross-sectional anatomy, Three-dimensional Imaging, Visible Human Projects
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