| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0382295 |
| utime |
20240103201411.8 |
| mtime |
20121105235959.9 |
| title
(primary) (eng) |
Evaluation of Screening Mammograms by Local Structural Mixture Models |
| specification |
| page_count |
11 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0382294 |
| ISBN |
978-80-01-05130-6 |
| title
|
Stochastic and Physical Monitoring Systems SPSM 2012 |
| page_num |
51-61 |
| publisher |
| place |
Praha |
| name |
Czech Technical University in Prague |
| year |
2012 |
|
|
| keyword |
Screening mammography |
| keyword |
Texture information |
| keyword |
Local statistical model |
| keyword |
Log-likelihood image |
| keyword |
Structural Gaussian mixture |
| author
(primary) |
| ARLID |
cav_un_auth*0101091 |
| name1 |
Grim |
| name2 |
Jiří |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0285165 |
| name1 |
Lee |
| name2 |
G. L. |
| country |
AU |
|
| source |
|
| cas_special |
| project |
| project_id |
GAP403/12/1557 |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0308953 |
|
| project |
| project_id |
GA102/08/0593 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0239567 |
|
| abstract
(eng) |
We consider the recently proposed evaluation of screening mammograms by local statistical models. The model is defined as a joint probability density of inside grey levels of a suitably chosen search window. We approximate the model density by a mixture of Gaussian densities. Having estimated the mixture parameters we calculate at all window positions the corresponding log-likelihood values which can be displayed as grey levels at the respective window centers. The resulting log-likelihood image closely correlates with the original mammogram and emphasizes the structural details. In this paper we try to enhance the log-likelihood images by using structural mixture model capable of suppressing the influence of noisy variables. |
| action |
| ARLID |
cav_un_auth*0284707 |
| name |
Stochastic and Physical Monitoring Systems |
| place |
Zlenice near Prague |
| dates |
25.06.2012-30.06.2012 |
| country |
CZ |
|
| reportyear |
2013 |
| RIV |
IN |
| num_of_auth |
2 |
| presentation_type |
ZP |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0212556 |
| arlyear |
2012 |
| mrcbU63 |
cav_un_epca*0382294 Stochastic and Physical Monitoring Systems SPSM 2012 978-80-01-05130-6 51 61 Praha Czech Technical University in Prague 2012 |
|