| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0433424 |
| utime |
20240103204835.6 |
| mtime |
20141106235959.9 |
| SCOPUS |
84947280888 |
| WOS |
000366592800064 |
| DOI |
10.1109/BMEI.2014.7002794 |
| title
(primary) (eng) |
Kinetic Modeling of the Dynamic PET Brain Data Using Blind Source Separation Methods |
| specification |
| page_count |
6 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0433423 |
| ISBN |
978-1-4799-5837-5 |
| title
|
The 2014 7th International Conference on BioMedical Engineering and Informatics |
| page_num |
244-249 |
| publisher |
| place |
Dalian, China |
| name |
IEEE press |
| year |
2014 |
|
|
| keyword |
blind source separation |
| keyword |
dynamic PET |
| keyword |
input function |
| keyword |
deconvolution |
| author
(primary) |
| ARLID |
cav_un_auth*0267768 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| full_dept |
Department of Adaptive Systems |
| share |
50 |
| name1 |
Tichý |
| name2 |
Ondřej |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101207 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| share |
50 |
| name1 |
Šmídl |
| name2 |
Václav |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0292734 |
| project_id |
GA13-29225S |
| agency |
GA ČR |
|
| abstract
(eng) |
Image-based definition of regions of interest is a typical prerequisite step for estimation of time-activity curves in dynamic positron emission tomography (PET). This procedure is done manually by a human operator and therefore suffers from subjective errors. Another such problem is to estimate the input function. It can be measured from arterial blood or it can be searched for a vascular structure on the images which is hard to be done, unreliable, and often impossible. In this study, we focus on blind source separation methods with no needs of manual interaction. Recently, we developed sparse blind source separation and deconvolution (S-BSS-vecDC) method for separation of original sources from dynamic medical data based on probability modeling and Variational Bayes approximation methodology. We apply the methods on dynamic brain PET data and application and comparison of our S-BSS-vecDC algorithm with those of similar assumptions are given. The S-BSS-vecDC algorithm is publicly available for download. |
| action |
| ARLID |
cav_un_auth*0308237 |
| name |
The 2014 7th International Conference on BioMedical Engineering and Informatics |
| dates |
14.10.2014-16.10.2014 |
| place |
Dalian |
| country |
CN |
|
| RIV |
BB |
| reportyear |
2015 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0238369 |
| confidential |
S |
| arlyear |
2014 |
| mrcbU14 |
84947280888 SCOPUS |
| mrcbU34 |
000366592800064 WOS |
| mrcbU63 |
cav_un_epca*0433423 The 2014 7th International Conference on BioMedical Engineering and Informatics 978-1-4799-5837-5 244 249 Dalian, China IEEE press 2014 |
|