bibtype K - Conference Paper (Czech conference)
ARLID 0436843
utime 20240103205246.6
mtime 20150106235959.9
title (primary) (eng) On Sparsity in Bayesian Blind Source Separation for Dynamic Medical Imaging
specification
page_count 2 s.
media_type P
serial
ARLID cav_un_epca*0436842
title Rektorysova Soutěž
page_num 20-21
publisher
place Praha
name Katedra metematiky, FSv ČVUT
year 2014
keyword blind source separation
keyword dynamic medical imaging
keyword sparsity constraint
author (primary)
ARLID cav_un_auth*0267768
name1 Tichý
name2 Ondřej
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2014/AS/tichy-0436843.pdf
cas_special
project
project_id GA13-29225S
agency GA ČR
ARLID cav_un_auth*0292734
abstract (eng) 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.
action
ARLID cav_un_auth*0311102
name Rektorysova Soutěž
place Praha
dates 3.12.2014
country CZ
reportyear 2015
RIV BB
num_of_auth 1
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0241894
confidential S
arlyear 2014
mrcbU63 cav_un_epca*0436842 Rektorysova Soutěž 20 21 Praha Katedra metematiky, FSv ČVUT 2014