0428540 20240903204447.920150129235959.9 84981362611 000378400800003 10.1080/21681163.2014.916229 11 s. E cav_un_epca*04285392168-11714135-145 blind source separation convolution dynamic medical imaging compartment modelling cav_un_auth*0267768 Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems 34 Tichý Ondřej UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101207 Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems 33 Šmídl Václav UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0211467 33 Šámal M. CZ http://library.utia.cas.cz/separaty/2014/AS/tichy-0428540.pdf cav_un_auth*0292734 GA13-29225S GA ČR Image-based definition of input function (IF) and organ function is a prerequisite for kinetic analysis of dynamic scintigraphy or positron emission tomography. This task is typically done manually by a human operator and suffers from low accuracy and reproducibility. We propose a probabilistic model based on physiological assumption that time – activity curves (TACs) arise as a convolution of an IF and tissue-specific kernels. The model is solved via the Variational Bayes estimation procedure and provides estimates of the IF, tissue-specific TACs and their related spatial distributions (images) as its results. The algorithm was tested with data of dynamic renal scintigraphy. The method was applied to the problem of differential renal function estimation and the IF estimation and the results are compared with competing techniques on datasets with 99 and 19 patients. The MATLAB implementation of the algorithm is available for download. BB 2015 3 4 A 4a 20231122140243.5 RVO:67985556 http://hdl.handle.net/11104/0234222 S 3+4 Article Engineering Biomedical 0.141 Q4 Q4 2016 Soubory v repozitáři: tichy-0428540.pdf 84981362611 SCOPUS 000378400800003 WOS cav_un_epca*0428539 Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2168-1171 2168-1171 Roč. 4 3-4 2016 135 145