生物医学中的光声成像
成像体模
生物医学工程
分割
血管侵犯
计算机科学
核医学
材料科学
人工智能
医学
癌症
光学
物理
内科学
作者
Mingjian Sun,Chao Li,Ningbo Chen,Hongxin Zhao,Liyong Ma,Chengbo Liu,Yi Shen,Riqiang Lin,Xiaojing Gong
出处
期刊:Photoacoustics
[Elsevier BV]
日期:2020-12-01
卷期号:20: 100212-100212
被引量:15
标识
DOI:10.1016/j.pacs.2020.100212
摘要
Quantitative analysis of tumor vessels is of great significance for tumor staging and diagnosis. Photoacoustic imaging (PAI) has been proven to be an effective way to visualize comprehensive tumor vascular networks in three-dimensional (3D) volume, while previous studies only quantified the vessels projected in one plane. In this study, tumor vessels were segmented and quantified in a full 3D framework. It had been verified in the phantom experiments that the 3D quantification results have better accuracy than 2D. Furthermore, in vivo vessel images were quantified by 2D and 3D quantification methods respectively. And the difference between these two results is significant. In this study, complete vessel segmentation and quantification method within a 3D framework was implemented, which showed obvious advantage in the analysis accuracy of 3D photoacoustic images, and potentially improve tumor study and diagnosis.
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