Donatas Sederevičius, M. Meilūnas, A. Ušinskas, J. Usinskiene
{"title":"人脑MRI灌注过程的建模","authors":"Donatas Sederevičius, M. Meilūnas, A. Ušinskas, J. Usinskiene","doi":"10.1109/AIEEE.2014.7020325","DOIUrl":null,"url":null,"abstract":"In the paper two models of the brain perfusion for dynamic susceptibility contrast magnetic resonance imaging technique are introduced. Estimation of the cerebral perfusion parameters is done by two approaches. Both approaches are based on non-linear regression method. Parametric maps of perfusion parameters are given and compared. In conclusion it is resumed what factors can effect the final results.","PeriodicalId":117147,"journal":{"name":"2014 IEEE 2nd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling of the MRI perfusion process of human head\",\"authors\":\"Donatas Sederevičius, M. Meilūnas, A. Ušinskas, J. Usinskiene\",\"doi\":\"10.1109/AIEEE.2014.7020325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper two models of the brain perfusion for dynamic susceptibility contrast magnetic resonance imaging technique are introduced. Estimation of the cerebral perfusion parameters is done by two approaches. Both approaches are based on non-linear regression method. Parametric maps of perfusion parameters are given and compared. In conclusion it is resumed what factors can effect the final results.\",\"PeriodicalId\":117147,\"journal\":{\"name\":\"2014 IEEE 2nd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 2nd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIEEE.2014.7020325\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 2nd Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIEEE.2014.7020325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modelling of the MRI perfusion process of human head
In the paper two models of the brain perfusion for dynamic susceptibility contrast magnetic resonance imaging technique are introduced. Estimation of the cerebral perfusion parameters is done by two approaches. Both approaches are based on non-linear regression method. Parametric maps of perfusion parameters are given and compared. In conclusion it is resumed what factors can effect the final results.