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	Diagnostické vyhodnocování screeningových mamogramů pomocí lokálních texturních modelů Grim, Jiří ; Somol, Petr We propose statistically based preprocessing of screening mammograms with the aim to emphasize suspicious areas. We estimate the local statistical texture model of a single mammogram in the form of multivariate Gaussian mixture. The probability density is estimated from the data obtained by pixelwise scanning of the mammogram with the search window. In the second phase, we evaluate the estimated density at each position of the window and display the corresponding log-likelihood value as a gray level at the window center. Light gray levels correspond to the typical parts of the image and the dark values reflect unusual places. The resulting log-likelihood image exactly correlates with the structural details of the original mammogram, emphasizes locations of similar properties by contour lines and may provide additional information to facilitate diagnostic interpretation. Detailed record
	A Monospectral Probabilistic Discrete Mixture Texture Model Grim, Jiří ; Haindl, Michal Detailed record
	Latent Structure Analysis for Categorical Data Grim, Jiří Detailed record
	Interactive presentation of socio-economic databases by means of probabilistic models Grim, Jiří ; Pudil, Pavel Detailed record
	Probabilistic Neural Networks Grim, Jiří Detailed record
	Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition Pudil, Pavel ; Novovičová, Jana ; Grim, Jiří Detailed record
	Discretization of probabilistic neural networks with bounded information loss Grim, Jiří Detailed record
	About the maximum information and maximum likelihood principles in neural networks Vajda, Igor ; Grim, Jiří Detailed record
	Mixture of experts architectures for neural networks as a special case of conditional expectation formula Grim, Jiří Detailed record
	Maximum-Likelihood Structuring of Probabilistic Neural Networks Grim, Jiří Detailed record

See also: similar author names
10	Grim, Jakub
1	Grim, Jan

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