bibtype C - Conference Paper (international conference)
ARLID 0454449
utime 20240103211644.6
mtime 20160215235959.9
SCOPUS 84962799507
WOS 000380431200025
DOI 10.1109/IWCIM.2015.7347085
title (primary) (eng) Classification of breast density in X-ray mammography
specification
page_count 5 s.
media_type E
serial
ARLID cav_un_epca*0454448
ISBN 978-1-4673-8457-5
title 2015 International Workshop on Computational Intelligence for Multimedia Understanding
page_num 1-5
publisher
place New York, NY,
name IEEE
year 2015
keyword Breast cancer
keyword breast density
keyword Mammography
keyword MRF
keyword ACR
keyword BI-RADS
author (primary)
ARLID cav_un_auth*0286710
full_dept (cz) Rozpoznávání obrazu
full_dept (eng) Department of Pattern Recognition
department (cz) RO
department (eng) RO
full_dept Department of Pattern Recognition
name1 Remeš
name2 Václav
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101093
full_dept (cz) Rozpoznávání obrazu
full_dept Department of Pattern Recognition
department (cz) RO
department RO
full_dept Department of Pattern Recognition
name1 Haindl
name2 Michal
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2016/RO/haindl-0454449.pdf
cas_special
project
ARLID cav_un_auth*0303439
project_id GA14-10911S
agency GA ČR
country CZ
abstract (eng) Breast density is an important cue to detect both the presence of suspicious cancerous masses and to predict future possibility for cancer development. A fast breast density classification method is presented and successfully tested on two state-of-the-art mammogram databases. The X-ray digital mammogram tissue texture is locally represented by the two-dimensional adaptive causal autoregressive spatial model and its parameters are used as the classification features.
action
ARLID cav_un_auth*0325650
name IWCIM 2015 International Workshop on Computational Intelligence for Multimedia Understanding
dates 29.10.2015-30.10.2015
place Praha
country CZ
RIV BD
reportyear 2016
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0257087
confidential S
arlyear 2015
mrcbU14 84962799507 SCOPUS
mrcbU34 000380431200025 WOS
mrcbU63 cav_un_epca*0454448 2015 International Workshop on Computational Intelligence for Multimedia Understanding 978-1-4673-8457-5 1 5 New York, NY, IEEE 2015