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

IF 1.5 4区医学 Q3 SURGERY Computer Assisted Surgery Pub Date : 2019-08-06 DOI:10.1080/24699322.2019.1649068

B. Liu, Simei Li, Jingyi Zhang, Qian Wu, Liang Yang, Wen Qi, Sijie Guan, Shuo Zhang, Jianxin Zhang

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引用次数: 1

Abstract

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.

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基于oneccut和相邻图像几何特征的可见人体切片分割方法框架

摘要作为近年来研究的热点问题，获得准确的3 可见人体计划（VHP）的D器官模型具有许多意义。因此，如何在大规模彩色切片图像数据集中提取感兴趣器官区域（ROI）成为亟待解决的问题。本文提出了一种基于OneCut算法和相邻图像几何特征的连续提取主要器官区域的方法框架。该框架主要包括两个部分：首先，OneCut算法用于分割当前图像中目标器官的ROI；其次，将前景图像（获得的ROI）腐蚀成几个种子点，将背景图像（除ROI外的其他区域）细化成骨架。然后，可以将获得的种子点和骨架传输并映射到下一个图像上，作为OneCut算法的输入。从而，可以在没有手动描绘的情况下连续处理序列化的切片图像。实验结果表明，提取的VHP器官是令人满意的。该方法框架可为其他相关应用提供良好的技术基础。

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来源期刊

Computer Assisted Surgery Medicine-Surgery

CiteScore

2.30

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： omputer Assisted Surgery aims to improve patient care by advancing the utilization of computers during treatment; to evaluate the benefits and risks associated with the integration of advanced digital technologies into surgical practice; to disseminate clinical and basic research relevant to stereotactic surgery, minimal access surgery, endoscopy, and surgical robotics; to encourage interdisciplinary collaboration between engineers and physicians in developing new concepts and applications; to educate clinicians about the principles and techniques of computer assisted surgery and therapeutics; and to serve the international scientific community as a medium for the transfer of new information relating to theory, research, and practice in biomedical imaging and the surgical specialties. The scope of Computer Assisted Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotactic procedures, surgery guided by intraoperative ultrasound or magnetic resonance imaging, image guided focused irradiation, robotic surgery, and any therapeutic interventions performed with the use of digital imaging technology.