Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

Abstract

A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub… (More)
DOI: 10.1186/1687-6180-2011-91

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Cite this paper

@article{QuintanillaDomnguez2011ImprovementFD, title={Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks}, author={Joel Quintanilla-Dom{\'i}nguez and Benjam{\'i}n Ojeda-Maga{\~n}a and Alexis Marcano-Cede{\~n}o and Maria Guadalupe Cortina-Januchs and Antonio Vega-Corona and Diego Andina}, journal={EURASIP J. Adv. Sig. Proc.}, year={2011}, volume={2011}, pages={91} }