{"title":"CT-guided automatic path planning for lung puncture","authors":"Jianquan Zhong, Jinyang Shen, Ling Tang, Ruizhi Hao, Jiayu Zhang, Yuhang Gong, Jing Zhang","doi":"10.1109/CCISP55629.2022.9974252","DOIUrl":null,"url":null,"abstract":"An automatic CT image-based path planning method for lung puncture surgery is proposed due to high failure rate, time consumption, and the high radiation dose of the existing percutaneous lung puncture surgery. The method described in this paper implements automatic organ segmentation of chest CT images. It defines six constraining conditions combined with clinical a priori knowledge to find the optimal puncture path using a multi-objective Pareto optimization method. The rationality and validity of the method were validated based on 25 sets of clinical lung mass data. Experimental results show that the optimal paths found by this system all meet the clinician's surgical requirements.","PeriodicalId":431851,"journal":{"name":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Communication, Image and Signal Processing (CCISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCISP55629.2022.9974252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
An automatic CT image-based path planning method for lung puncture surgery is proposed due to high failure rate, time consumption, and the high radiation dose of the existing percutaneous lung puncture surgery. The method described in this paper implements automatic organ segmentation of chest CT images. It defines six constraining conditions combined with clinical a priori knowledge to find the optimal puncture path using a multi-objective Pareto optimization method. The rationality and validity of the method were validated based on 25 sets of clinical lung mass data. Experimental results show that the optimal paths found by this system all meet the clinician's surgical requirements.