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On Sparsity in Bayesian Blind Source Separation for Dynamic Medical Imaging
- 1.0436843 - ÚTIA 2015 CZ eng K - Conference Paper (Czech conference)
Tichý, Ondřej
On Sparsity in Bayesian Blind Source Separation for Dynamic Medical Imaging.
Rektorysova Soutěž. Praha: Katedra metematiky, FSv ČVUT, 2014, s. 20-21.
[Rektorysova Soutěž. Praha (CZ), 3.12.2014]
R&D Projects: GA ČR GA13-29225S
Institutional support: RVO:67985556
Keywords : blind source separation * dynamic medical imaging * sparsity constraint
Subject RIV: BB - Applied Statistics, Operational Research
http://library.utia.cas.cz/separaty/2014/AS/tichy-0436843.pdf
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.
Permanent Link: http://hdl.handle.net/11104/0241894
Number of the records: 1