0383332 20240103201518.920121130235959.9 10 s. P cav_un_epca*0384152978-80-01-05138-21-10PrahaČVUT v Praze2012 Blind Source Separation Factor Analysis Convolution Regions of Interest Image Sequence 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/2012/AS/tichy-model consideration for blind source separation of medical image sequences.pdf The problem of functional analysis of medical image sequences is studied. The obtained images are assumed to be a superposition of images of underlying biological organs. This is commonly modeled as a Factor Analysis (FA) model. However, this model alone allows for biologically impossible solutions. Therefore, we seek additional biologically motivated assumptions that can be incorporated into the model to yield better solutions. In this paper, we review additional assumptions such as convolution of time activity, regions of interest selection, and noise analysis. All these assumptions can be incorporated into the FA model and their parameters estimated by the Variation Bayes estimation procedure. We compare these assumptions and discuss their influence on the resulting decomposition from diagnostic point of view. The algorithms are tested and demonstrated on real data from renal scintigraphy; however, the methodology can be used in any other imaging modality. cav_un_auth*0285592 Doktorandské dny 2012 Praha 16.11.2012-23.11.2012 CZ 2013 BB 1 PR RVO:67985556 http://hdl.handle.net/11104/0213299 2012 cav_un_epca*0384152 Doktorandské dny 2012 978-80-01-05138-2 1 10 Praha ČVUT v Praze 2012