0454449 - ÚTIA 2016 RIV US eng C - Conference Paper (international conference)
Remeš, Václav - Haindl, Michal
Classification of breast density in X-ray mammography.
2015 International Workshop on Computational Intelligence for Multimedia Understanding. New York, NY,: IEEE, 2015, s. 1-5. ISBN 978-1-4673-8457-5.
[IWCIM 2015 International Workshop on Computational Intelligence for Multimedia Understanding. Praha (CZ), 29.10.2015-30.10.2015]
R&D Projects: GA ČR(CZ) GA14-10911S
Institutional support: RVO:67985556
Keywords : Breast cancer * breast density * Mammography * MRF * ACR * BI-RADS
Subject RIV: BD - Theory of Information
Result website:
http://library.utia.cas.cz/separaty/2016/RO/haindl-0454449.pdf

DOI: https://doi.org/10.1109/IWCIM.2015.7347085

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.
Permanent Link: http://hdl.handle.net/11104/0257087