Resumen

GALLEGO-ORTIZ, Nicolás  y  FERNANDEZ-MC-CANN, David. Statistical Texture Model for mass Detection in Mammography. rev.ing. [online]. 2013, n.39, pp.12-16. ISSN 0121-4993.

In the context of image processing algorithms for mass detection in mammography, texture is a key feature to be used to distinguish abnormal tissue from normal tissue. Recently, a texture model based on a multivariate gaussian mixture was proposed, of which the parameters are lear-ned in an unsupervised way from the pixel intensities of images. The model produces images that are probabilistic maps of texture normality and it was proposed as a visua-lization aid for diagnostic by clinical experts. In this paper, the usability of the model is studied for automatic mass de-tection. A segmentation strategy is proposed and evaluated using 79 mammography cases.

Palabras clave : Biomedical Engineering; Breast-Cancer; Mathematical; Models; Radiodiagnostic; Statistical Methods.

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