Detection of Microcalcifications in Mammograms by the Combination of a Neural Detector and Multiscale Feature Enhancement

Authors:
Diego Andina;Antonio Vega-Corona
Affiliations:
-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Year:
2001

Citing 2
Cited 2

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Feature Vectors Generation for Detection of Microcalcifications in Digitized Mammography Using Neural Networks

IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods

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Abstract

We propose a two steps method for the automatic classification of microcalcifications in Mammograms. The first step performs the improvement of the visuaalization of any abnormal lesion through feature enhancement based in multiscale wavelet representations of the mammographic images. In a second step the automatic recognition of microcalcifications is achived by the application of a Neural Network optimized in the Neyman-Pearson sense. That means that the Neural Network presents a controlled and very low probability of classifying abnormal images as normal.