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 |
|
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 |
|