A Segmentation Method of Serialized Human Body Slices Based on Matting Strategy and Skeleton Extraction

Bin Liu; Zhengyang Wu; Chenlu Wang; Shiyu Pang; Jingzhu Pei; Jianxin Zhang; Liang Yang

doi:10.2174/1573405620666230515090618

A Segmentation Method of Serialized Human Body Slices Based on Matting Strategy and Skeleton Extraction

Curr Med Imaging. 2023 May 15. doi: 10.2174/1573405620666230515090618. Online ahead of print.

Authors

Bin Liu^{1

2}, Zhengyang Wu¹, Chenlu Wang¹, Shiyu Pang¹, Jingzhu Pei¹, Jianxin Zhang^{2

3}, Liang Yang¹

Affiliations

¹ International School of Information Science & Engineering (DUT-RUISE), Dalian University of Technology, Dalian, 116620 China.
² DUT-RU Co-Research Center of Advanced ICT for Active Life, Dalian University of Technology, Dalian, 116620 China.
³ Key Lab of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, 116620 China.

PMID: 37189280
DOI: 10.2174/1573405620666230515090618

Abstract

Introduction: In this paper, a semiautomatic image segmentation method for the serialized body slices of the Visible Human Project (VHP) is proposed.

Method: In our method, we first verified the effectiveness of the shared matting method for the VHP slices and utilized it to segment a single image. Then, to meet the need for the automatic segmentation of serialized slice images, a method based on the parallel refinement method and flood-fill method was designed. The ROI (region of interest) image of the next slice can be extracted by using the skeleton image of the ROI in the current slice.

Result: Utilizing this strategy, the color slice images of the Visible Human body can be continuously and serially segmented. This method is not complex but is rapid and automatic with less manual participation.

Conclusion: The experimental results show that the primary organs of the Visible Human body can be accurately extracted.

Keywords: Image Matting; Organ Extraction; ROI; Serialized Segmentation; Visible Human; data.