Spatio-temporal image analysis for longitudinal and time-series image data : Second International Workshop, STIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1, 2012, proceedings. STIA (Conference) (2nd : 2012 : Nic...最新文献
Pub Date : 2012-10-01DOI: 10.1007/978-3-642-33555-6_11
Nicha Chitphakdithai, Veronica L Chiang, James S Duncan
The treatment of metastatic brain tumors with stereotactic radiosurgery requires that the clinician first locate the tumors and measure their volumes. Thoroughly searching a patient scan for brain tumors and delineating the lesions can be a long and difficult task when done manually and is also prone to human error. In this paper, we present an automated method for detecting changes in brain tumor lesions over longitudinal scans to aide the clinician's task of determining tumor volumes. Our approach jointly registers the current image with a previous scan while estimating changes in intensity correspondences due to tumor growth or regression. We combine the label map with correspondence changes with tumor segmentations from a previous scan to estimate the metastases in the new image. Alignment and tumor tracking results show promise on 28 registrations using real patient data.
{"title":"Tracking Metastatic Brain Tumors in Longitudinal Scans via Joint Image Registration and Labeling.","authors":"Nicha Chitphakdithai, Veronica L Chiang, James S Duncan","doi":"10.1007/978-3-642-33555-6_11","DOIUrl":"10.1007/978-3-642-33555-6_11","url":null,"abstract":"<p><p>The treatment of metastatic brain tumors with stereotactic radiosurgery requires that the clinician first locate the tumors and measure their volumes. Thoroughly searching a patient scan for brain tumors and delineating the lesions can be a long and difficult task when done manually and is also prone to human error. In this paper, we present an automated method for detecting changes in brain tumor lesions over longitudinal scans to aide the clinician's task of determining tumor volumes. Our approach jointly registers the current image with a previous scan while estimating changes in intensity correspondences due to tumor growth or regression. We combine the label map with correspondence changes with tumor segmentations from a previous scan to estimate the metastases in the new image. Alignment and tumor tracking results show promise on 28 registrations using real patient data.</p>","PeriodicalId":90731,"journal":{"name":"Spatio-temporal image analysis for longitudinal and time-series image data : Second International Workshop, STIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1, 2012, proceedings. STIA (Conference) (2nd : 2012 : Nic...","volume":"7570 ","pages":"124-136"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559745/pdf/nihms-996653.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37318622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1007/978-3-642-33555-6_7
Manasi Datar, Prasanna Muralidharan, Abhishek Kumar, Sylvain Gouttard, Joseph Piven, Guido Gerig, Ross Whitaker, P Thomas Fletcher
In this paper, we propose a new method for longitudinal shape analysis that fits a linear mixed-effects model, while simultaneously optimizing correspondences on a set of anatomical shapes. Shape changes are modeled in a hierarchical fashion, with the global population trend as a fixed effect and individual trends as random effects. The statistical significance of the estimated trends are evaluated using specifically designed permutation tests. We also develop a permutation test based on the Hotelling T2 statistic to compare the average shapes trends between two populations. We demonstrate the benefits of our method on a synthetic example of longitudinal tori and data from a developmental neuroimaging study.
{"title":"Mixed-Effects Shape Models for Estimating Longitudinal Changes in Anatomy.","authors":"Manasi Datar, Prasanna Muralidharan, Abhishek Kumar, Sylvain Gouttard, Joseph Piven, Guido Gerig, Ross Whitaker, P Thomas Fletcher","doi":"10.1007/978-3-642-33555-6_7","DOIUrl":"https://doi.org/10.1007/978-3-642-33555-6_7","url":null,"abstract":"<p><p>In this paper, we propose a new method for longitudinal shape analysis that fits a linear mixed-effects model, while simultaneously optimizing correspondences on a set of anatomical shapes. Shape changes are modeled in a hierarchical fashion, with the global population trend as a fixed effect and individual trends as random effects. The statistical significance of the estimated trends are evaluated using specifically designed permutation tests. We also develop a permutation test based on the Hotelling <i>T</i><sup>2</sup> statistic to compare the average shapes trends between two populations. We demonstrate the benefits of our method on a synthetic example of longitudinal tori and data from a developmental neuroimaging study.</p>","PeriodicalId":90731,"journal":{"name":"Spatio-temporal image analysis for longitudinal and time-series image data : Second International Workshop, STIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1, 2012, proceedings. STIA (Conference) (2nd : 2012 : Nic...","volume":"7570 ","pages":"76-87"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/978-3-642-33555-6_7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32909063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spatio-temporal image analysis for longitudinal and time-series image data : Second International Workshop, STIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1, 2012, proceedings. STIA (Conference) (2nd : 2012 : Nic...
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号