M. Listewnik, H. Piwowarska-Bilska, K. Safranow, Jacek Iwanowski, M. Laszczyńska, M. Chosia, M. Ostrowski, B. Birkenfeld, P. Mazurek
{"title":"Multivariate generalized Gaussian function mixture for volume modeling of parathyroid glands","authors":"M. Listewnik, H. Piwowarska-Bilska, K. Safranow, Jacek Iwanowski, M. Laszczyńska, M. Chosia, M. Ostrowski, B. Birkenfeld, P. Mazurek","doi":"10.1109/MMAR.2017.8046974","DOIUrl":null,"url":null,"abstract":"The main contribution of this paper is the proposal of volume modeling of parathyroid gland. Multivariate generalized Gaussian distribution (Multivariate GGD) mixture is assumed. Random walk optimization algorithm is applied for the estimation of parameters. There are 800 synthetic test cases applied for the evaluation of algorithm properties. Example result for real SPECT data are also shown. The essential is the computation time, so GPGPU implementation is proposed for reduction of processing time. Obtained parameters of mixture are required for further analysis of relation to patient data.","PeriodicalId":189753,"journal":{"name":"2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2017.8046974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The main contribution of this paper is the proposal of volume modeling of parathyroid gland. Multivariate generalized Gaussian distribution (Multivariate GGD) mixture is assumed. Random walk optimization algorithm is applied for the estimation of parameters. There are 800 synthetic test cases applied for the evaluation of algorithm properties. Example result for real SPECT data are also shown. The essential is the computation time, so GPGPU implementation is proposed for reduction of processing time. Obtained parameters of mixture are required for further analysis of relation to patient data.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
