On Sparsity in Bayesian Blind Source Separation for Dynamic Medical Imaging

0436843 20240103205246.620150106235959.9 On Sparsity in Bayesian Blind Source Separation for Dynamic Medical Imaging 2 s. P cav_un_epca*0436842Rektorysova Soutěž20-21PrahaKatedra metematiky, FSv ČVUT2014 blind source separation dynamic medical imaging sparsity constraint cav_un_auth*0267768 Tichý Ondřej Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/AS/tichy-0436843.pdf GA13-29225S GA ČR cav_un_auth*0292734 Dynamic medical imaging is concerned with acquisition and analysis of a sequence of images of the same region of a body during time. In nuclear medicine, each pixel of an image is the sum of particles coming from an applied radioactive tracer from the body in a specific time-interval. Hence, each observed image is a superposition of an unknown number of underlaying organ images. The aim of blind source separation is to separate the images of biologic organs and related time-activity curves from the sequence of images. cav_un_auth*0311102 Rektorysova Soutěž Praha 3.12.2014 CZ 2015 BB 1 PR RVO:67985556 http://hdl.handle.net/11104/0241894 S 2014 cav_un_epca*0436842 Rektorysova Soutěž 20 21 Praha Katedra metematiky, FSv ČVUT 2014