Publication details

Diagnostic Enhancement of Screening Mammograms by Means of Local Texture Models

Research Report

Grim Jiří, Somol Petr


publisher: ÚTIA AV ČR, (Praha 2008)

edition: Research Report 2217

research: CEZ:AV0Z10750506

project(s): 1M0572, GA MŠk, 2C06019, GA MŠk

keywords: Distribution mixtures, Screening Mammography, Local Statistical Models, Computer assisted screening and diagnosis, Visualization of biomedical data

abstract (eng):

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.

abstract (cze):

Předmětem práce je návrh diagnostického vyhodnocování screeningových mamogramů pomocí lokálního statistického modelu. Cílem metody je zvýraznění diagnosticky významných detailů mamogramu. Výsledkem zpracování je tzv. věrohodnostní obraz původního mamogramu, který by v kombinaci s původním snímkem mohl usnadnit práci radiologa.

RIV: IN