Creation of a female and male segmentation dataset based on Chinese Visible Human (CVH)

Abstract

Objective: Segmentation is a necessary step when creating realistic three-dimensional (3D) models. In order to build 3D models of whole body structures and have a wider lateral application, the thin sectional anatomical images of the Chinese Visible Human (CVH) dataset should be segmented. The more detailed structures are segmented to provide greater potential for wider application of the segmented images.

Materials and methods: All the images based on the CVH male and female dataset were segmented semi-automatically using PHOTOSHOP software. This research lasted about 7 years.

Result: In this study, 869 structures of CVH male and 860 structures of CVH female were semi-automatically segmented, and the formats for the segmented color-filled image data were PSD and PNG. In these segmented structures, nearly all skeletal muscles included muscle belly and tendon, and hollow organs included their organ walls and their lumen. Most nerve trunks, small arteries, lymph nodes, and lymph ducts were also segmented. Many surface-rendering and volume-rendering organ models were created using these segmented images.

Conclusion: The CVH male and female images represent the normal Asian population. After segmentation, the images can be reconstructed directly in 3D and greatly facilitate the biological modeling of physical and physiological information, a great help in improving medical and biological science in China.