A visible human body slice segmentation method framework based on OneCut and adjacent image geometric features

Abstract

As a recent research hot issue, obtaining the accurate 3 D organ models of Visible Human Project (VHP) has many significances. Therefore, how to extract the organ regions of interest (ROI) in the large-scale color slice image data set has become an urgent issue to be solved. In this paper, we propose a method framework based on OneCut algorithm and adjacent image geometric features to continuously extract the main organ regions is proposed. This framework mainly contains two parts: firstly, the OneCut algorithm is used to segment the ROI of target organ in the current image; secondly, the foreground image (obtained ROI) is corroded into several seed points and the background image (other region except for ROI) is refined into a skeleton. Then the obtained seed points and skeleton can be transmitted and mapped onto the next image as the input of OneCut algorithm. Thereby, the serialized slice images can be processed continuously without manual delineating. The experimental results show that the extracted VHP organs are satisfactory. This method framework may provide well technic foundation for other related application.

Keywords:

• Visible Human Project
• color image segmentation
• OneCut
• skeleton

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [Nos. 61572101, 61300085].