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

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 propos...

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Bibliographic Details
Main Authors: Bin Liu, Simei Li, Jingyi Zhang, Qianwen Wu, Liang Yang, Wen Qi, Sijie Guan, Shuo Zhang, Jianxin Zhang
Format: Article
Language:English
Published: Taylor & Francis Group 2019-10-01
Series:Computer Assisted Surgery
Subjects:
Online Access:http://dx.doi.org/10.1080/24699322.2019.1649068
Description
Summary: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.
ISSN:2469-9322