Advanced Sectioned Images of a Cadaver Head with Voxel Size of 0.04 mm
10.3346/jkms.2019.34.e218
- Author:
Beom Sun CHUNG
1
;
Miran HAN
;
Donghwan HAR
;
Jin Seo PARK
Author Information
1. Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.
- Publication Type:Original Article
- Keywords:
Cadaver;
Cross-Sectional Anatomy;
Diffusion Tensor Imaging;
Head;
Visible Human Project
- MeSH:
Anatomy, Cross-Sectional;
Brain;
Cadaver;
Diffusion;
Diffusion Tensor Imaging;
Female;
Head;
Humans;
White Matter
- From:Journal of Korean Medical Science
2019;34(34):e218-
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND: The sectioned images of a cadaver head made from the Visible Korean project have been used for research and educational purposes. However, the image resolution is insufficient to observe detailed structures suitable for experts. In this study, advanced sectioned images with higher resolution were produced for the identification of more detailed structures. METHODS: The head of a donated female cadaver was scanned for 3 Tesla magnetic resonance images and diffusion tensor images (DTIs). After the head was frozen, the head was sectioned serially at 0.04-mm intervals and photographed repeatedly using a digital camera. RESULTS: On the resulting 4,000 sectioned images (intervals and pixel size, 0.04 mm³; color depth, 48 bits color; a file size, 288 Mbytes), minute brain structures, which can be observed not on previous sectioned images but on microscopic slides, were observed. The voxel size of this study (0.04 mm³) was very minute compared to our previous study (0.1 mm³; resolution, 4,368 × 2,912) and Visible Human Project of the USA (0.33 mm³; resolution, 2,048 × 2,048). Furthermore, the sectioned images were combined with tractography of the DTIs to elucidate the white matter with high resolution and the actual color of the tissue. CONCLUSION: The sectioned images will be used for diverse research, including the applications for the cross sectional anatomy and three-dimensional models for virtual experiments.
