SVM and Neural Networks comparison in mammographic CAD
Carlos J. Garcı́a-Orellana, Ramón Gallardo–Caballero, Miguel Macías Macías, Horacio M. González–Velasco · Conference proceedings · 2007
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).