A. H. Foruzan, Yenwei Chen, R. Zoroofi, M. Kaibori
{"title":"Analysis of CT Images of Liver for Surgical Planning","authors":"A. H. Foruzan, Yenwei Chen, R. Zoroofi, M. Kaibori","doi":"10.5923/J.AJBE.20120202.05","DOIUrl":null,"url":null,"abstract":"We developed a Computer Assisted Surgery system which prepared a virtual environment for a physician to interact with the liver and decide on the therapy planning. It was composed of three modules: liver segmentation, vessel extraction, and simulator. We proposed a semi-automatic method to segment the liver. Hepatic veins, portal veins, and he- patic arteries were extracted from multi-phase CT datasets. The simulator visualized the segmented objects and provided for a physician a virtual scalpel to cut the liver. Initially, a transparent view of the liver was shown to the physician that revealed the location of the vascular structures. During the surgery, a toggling option made it possible to switch between a transparent and an opaque view. The width, height, and depth of the cut could be changed by user interaction. The proposed system is a framework which can later be extended to a complete system for analysis of hepatic diseases and therapy planning.","PeriodicalId":7620,"journal":{"name":"American Journal of Biomedical Engineering","volume":"80 1","pages":"23-28"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5923/J.AJBE.20120202.05","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We developed a Computer Assisted Surgery system which prepared a virtual environment for a physician to interact with the liver and decide on the therapy planning. It was composed of three modules: liver segmentation, vessel extraction, and simulator. We proposed a semi-automatic method to segment the liver. Hepatic veins, portal veins, and he- patic arteries were extracted from multi-phase CT datasets. The simulator visualized the segmented objects and provided for a physician a virtual scalpel to cut the liver. Initially, a transparent view of the liver was shown to the physician that revealed the location of the vascular structures. During the surgery, a toggling option made it possible to switch between a transparent and an opaque view. The width, height, and depth of the cut could be changed by user interaction. The proposed system is a framework which can later be extended to a complete system for analysis of hepatic diseases and therapy planning.