SVM and Neural Networks comparison in mammographic CAD

@article{GarciaOrellana2007SVMAN,
  title={SVM and Neural Networks comparison in mammographic CAD},
  author={C. J. Garcia-Orellana and Ramon Gallardo-Caballero and Miguel Macias-Macias and Horacio M. Gonzalez-Velasco},
  journal={2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2007},
  pages={3204-3207}
}
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). 

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Showing 1-10 of 13 references

The Nature of Statistical Learning Theory

Statistics for Engineering and Information Science • 2000
View 11 Excerpts
Highly Influenced

CAD System for Detecting Clustered Microcalcifications in Digital Mammograms using Independent Component Analysis and Neural Network

Jun Zhenga, Emma Regentovab, +3 authors Hideya Takeob
International Journal of Computer Assisted Radiology and Surgery • 2006
View 1 Excerpt

The advisability of the adoption of a law that would expand the definition of mammography screening to include the review of x-ray examinations by use of a computer aided detection device

G. V. Serio, A. C. Novello
Technical report, • 2003
View 1 Excerpt

Computer aided diagnosis of breast cancer in digitized mammograms.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society • 2002
View 3 Excerpts

puter aided diagnosis of breast cancer in digitized mammograms

A. Koutras I. Christoyianni, E. Dermatas
Computerized Medical Imaging and Graphics • 2001

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