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David Fernández-Mc-Cann ;Revista de Ingeniería 2013, (39)

Author: Nicolás Gallego-Ortiz

Source: http://www.redalyc.org/


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Revista de Ingeniería ISSN: 0121-4993 reingeri@uniandes.edu.co Universidad de Los Andes Colombia Gallego-Ortiz, Nicolás; Fernández-Mc-Cann, David Statistical Texture Model for mass Detection in Mammography Revista de Ingeniería, núm.
39, julio-diciembre, 2013, pp.
12-16 Universidad de Los Andes Bogotá, Colombia Available in: http:--www.redalyc.org-articulo.oa?id=121030106002 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative 12 SECCIÓN TÉCNICA Statistical Texture Model for mass Detection in Mammography Modelo estadístico de textura para detección de masas en mamografía Nicolás Gallego-Ortiz (1), David Fernández-Mc-Cann (2) (1) Ms.C en Ingeniería.
nicgallego@ieee.org (2) h.D.
en Telecomunicaciones.
rofesor Asociado.
Universidad de Antio uia.
Medellín, Colombia.
dfernan@udea.edu.co ecibido 30 de noviembre de 2012.
Modi cado 1 de septiembre de 2013.
Aprobado 1 de octubre de 2013. Key words Biomedical Engineering, Breast-Cancer, Mathematical Models, Radiodiagnostic, Statistical Methods. Palabras clave Ingeniería Biomédica, cáncer de seno, métodos estadísticos, modelos matemáticos, radiodiagnóstico. Abstract 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 learned 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 visualization aid for diagnostic by clinical experts.
In this paper, the usability of the model is studied for automatic mass detection.
A segmentation strategy is pro...





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