0322909 20240103191500.120090422235959.9 000264397100007 10.1109/TIP.2008.2011168 9 s. cav_un_epca*02532351057-7149184 (2009)765-773Institute of Electrical and Electronics Engineers Screening mammography texture information local statistical model Gaussian mixture cav_un_auth*0101091 Grim Jiří UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101197 Somol Petr UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101093 Haindl Michal UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0050523 Daneš J. CZ GA102/07/1594 GA ČR cav_un_auth*0228611 GA102/08/0593 GA ČR cav_un_auth*0239567 1M0572 GA MŠk cav_un_auth*0001814 2C06019 GA MŠk CZ cav_un_auth*0216518 CEZ:AV0Z10750506 We propose a new approach to diagnostic evaluation of screening mammograms based on local statistical texture models. The local evaluation tool has the form of a multivariate probability density of gray levels in a suitably chosen search window. First the density function in the form of Gaussian mixture is estimated from data obtained by scanning of the mammogram with the search window. Then we evaluate the estimated mixture at each position and display the corresponding log-likelihood value as a gray level at the window center. The resulting log-likelihood image closely correlates with the structural details of the original mammogram and emphasizes unusual places. We assume that, in parallel use, the log-likelihood image may provide additional information to facilitate the identification of malignant lesions as untypical locations of high novelty. Předmětem článku je návrh nové metody vyhodnocování mamomagramů pomocí lokálního statistického modelu. Výsledkem zpracování mamogramu je věrohodnostní transformace původního mamogramu, na které jsou zvýrazněna neobvyklá místa se zvýšenou pravděpodobností výskytu patologických změn. 2009 BB http://hdl.handle.net/11104/0171042 4.139 0.248 7.6 0.03222 1.408 11472 214 156 3.178 33.51 4.81 2009 000264397100007 WOS cav_un_epca*0253235 IEEE Transactions on Image Processing 1057-7149 1941-0042 Roč. 18 č. 4 2009 765 773 Institute of Electrical and Electronics Engineers