{"title":"A simple respiratory motion analysis method for chest tomosynthesis","authors":"Hua Zhang, X. Tao, G. Qin, Jianhua Ma, Qianjin Feng, Wufan Chen","doi":"10.1109/ISBI.2017.7950569","DOIUrl":null,"url":null,"abstract":"Chest tomosynthesis (CTS) is a newly developed imaging technique which provides pseudo-3D volume anatomical information of thorax from limited angle projections and therefore improves the visibility of anatomy without so much increase on radiation dose compared to the chest radiography (CXR). However, one of the relatively common problems in CTS is the respiratory motion of patient during image acquisition, which negatively impacts the detectability. In this paper, we propose a sin-quadratic model to analyze the respiratory motion during CTS scanning, which is a real time method that generates the respiratory signal by directly extracting the motion of diaphragm during data acquisition. According to the extracted respiratory signal, physicians could re-scan the patient immediately or conduct motion free CTS image reconstruction for patients that could not hold their breath perfectly during the scan time. The effectiveness of the proposed model was demonstrated with both the simulated phantom data and the real patient data.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":"26 6 1","pages":"498-501"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2017.7950569","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
Chest tomosynthesis (CTS) is a newly developed imaging technique which provides pseudo-3D volume anatomical information of thorax from limited angle projections and therefore improves the visibility of anatomy without so much increase on radiation dose compared to the chest radiography (CXR). However, one of the relatively common problems in CTS is the respiratory motion of patient during image acquisition, which negatively impacts the detectability. In this paper, we propose a sin-quadratic model to analyze the respiratory motion during CTS scanning, which is a real time method that generates the respiratory signal by directly extracting the motion of diaphragm during data acquisition. According to the extracted respiratory signal, physicians could re-scan the patient immediately or conduct motion free CTS image reconstruction for patients that could not hold their breath perfectly during the scan time. The effectiveness of the proposed model was demonstrated with both the simulated phantom data and the real patient data.