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SVM and Neural Networks comparison in mammographic CAD (2007) PDF
Título:SVM and Neural Networks comparison in mammographic CAD
Autores: Carlos J. García-Orellana, Ramón Gallardo-Caballero, Miguel Macías-Macías and Horacio González-Velasco

Tipo: 

Poster

Congreso:

29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publicación: Libro de Actas
Lugar:Lyon (Francia)
Año:2007
Abstract:The purpose of this work is to compare the performance of Support Vector Machines (SVM) and Multi-Layer Perceptron (MLP) in the task of detection and diagnosis of microcalcification clusters in mammograms (MCCs). As data source, the “Digital Database for Screening Mammography” (DDSM) was used. The results show a similar performance for SVM and MLP, in both tasks, detection and diagnosis (slightly better for MLP in detection).