{"title":"Methods for abdominal respiratory motion tracking.","authors":"Dominik Spinczyk, Adam Karwan, Marcin Copik","doi":"10.3109/10929088.2014.891657","DOIUrl":null,"url":null,"abstract":"<p><p>Non-invasive surface registration methods have been developed to register and track breathing motions in a patient's abdomen and thorax. We evaluated several different registration methods, including marker tracking using a stereo camera, chessboard image projection, and abdominal point clouds. Our point cloud approach was based on a time-of-flight (ToF) sensor that tracked the abdominal surface. We tested different respiratory phases using additional markers as landmarks for the extension of the non-rigid Iterative Closest Point (ICP) algorithm to improve the matching of irregular meshes. Four variants for retrieving the correspondence data were implemented and compared. Our evaluation involved 9 healthy individuals (3 females and 6 males) with point clouds captured in opposite breathing phases (i.e., inhalation and exhalation). We measured three factors: surface distance, correspondence distance, and marker error. To evaluate different methods for computing the correspondence measurements, we defined the number of correspondences for every target point and the average correspondence assignment error of the points nearest the markers.</p>","PeriodicalId":50644,"journal":{"name":"Computer Aided Surgery","volume":"19 1-3","pages":"34-47"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/10929088.2014.891657","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Aided Surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3109/10929088.2014.891657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2014/4/10 0:00:00","PubModel":"Epub","JCR":"Q","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 17
Abstract
Non-invasive surface registration methods have been developed to register and track breathing motions in a patient's abdomen and thorax. We evaluated several different registration methods, including marker tracking using a stereo camera, chessboard image projection, and abdominal point clouds. Our point cloud approach was based on a time-of-flight (ToF) sensor that tracked the abdominal surface. We tested different respiratory phases using additional markers as landmarks for the extension of the non-rigid Iterative Closest Point (ICP) algorithm to improve the matching of irregular meshes. Four variants for retrieving the correspondence data were implemented and compared. Our evaluation involved 9 healthy individuals (3 females and 6 males) with point clouds captured in opposite breathing phases (i.e., inhalation and exhalation). We measured three factors: surface distance, correspondence distance, and marker error. To evaluate different methods for computing the correspondence measurements, we defined the number of correspondences for every target point and the average correspondence assignment error of the points nearest the markers.
期刊介绍:
The scope of Computer Aided Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotaxic procedures, surgery guided by ultrasound, image guided focal irradiation, robotic surgery, and other therapeutic interventions that are performed with the use of digital imaging technology.