Title :
SVM and Neural Networks comparison in mammographic CAD
Author :
Garcia-Orellana, C.J. ; Gallardo-Caballero, R. ; Macias-Macias, M. ; Gonzalez-Velasco, H.
Author_Institution :
Univ. de Extremadura, Badajoz
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).
Keywords :
biological organs; cancer; mammography; medical image processing; multilayer perceptrons; support vector machines; visual databases; breast cancer; digital database; mammographic CAD; microcalcification cluster detection; microcalcification cluster diagnosis; multilayer perceptron; neural networks; screening mammography; support vector machines; Breast cancer; Cancer detection; Coronary arteriosclerosis; Independent component analysis; Lesions; Mammography; Neural networks; Proposals; Support vector machines; Tumors; Algorithms; Breast Diseases; Calcinosis; Expert Systems; Female; Humans; Mammography; Neural Networks (Computer); Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353011
