{"title":"Inter-subject variability of respiratory motion from 4D MRI","authors":"Ashrani Aizzuddin Abd Rahni, E. Lewis, K. Wells","doi":"10.1109/ICBAPS.2015.7292225","DOIUrl":null,"url":null,"abstract":"Respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. Existing approaches for respiratory motion management are often based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper aims to present a more in depth analysis of respiratory motion based on 4D MRI, which can then be integrated into motion correction approaches in image acquisition or image based EBRT. In this paper we analyse the respiratory motion of organs for five volunteers on a per-organ basis, separately for each volunteer and together comparatively. We also compare with a separate study of respiratory motion for 20 patients. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature and a similar process can be used in future to extract and quantify respiratory motion on a larger dataset.","PeriodicalId":243293,"journal":{"name":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBAPS.2015.7292225","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
Respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. Existing approaches for respiratory motion management are often based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper aims to present a more in depth analysis of respiratory motion based on 4D MRI, which can then be integrated into motion correction approaches in image acquisition or image based EBRT. In this paper we analyse the respiratory motion of organs for five volunteers on a per-organ basis, separately for each volunteer and together comparatively. We also compare with a separate study of respiratory motion for 20 patients. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature and a similar process can be used in future to extract and quantify respiratory motion on a larger dataset.