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Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines

Opened Access Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines

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Autor: Martínez Álvarez, Francisco
Troncoso Lora, Alicia
Riquelme Santos, José Cristóbal
Aguilar Ruiz, Jesús Salvador
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2007
Publicado en: Computer-Based Medical Systems, 2007. CBMS '07. Twentieth IEEE International Symposium, pp. 141-146 (2007)
Tipo de documento: Capítulo de Libro
Resumen: Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved to be the most effective way to combat it. This work is focused on developing an integral tool able to detect microcalcifications in mammographies, since the presence of these particles is a clear symptom of an incipient cancer. The proposed approach combines two techniques successfully used in other areas separately, such as linear pixel prediction and support-vector machines, in order to obtain almost perfect prediction accuracy. Moreover, a filter has been designed with the aim of decrease the processing time. The result verges on 96% of hits, improving previous works by 6%, on average.
Tamaño: 366.6Kb
Formato: PDF

URI: http://hdl.handle.net/11441/39735

DOI: http://dx.doi.org/10.1109/CBMS.2007.38

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