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Journal of Electronic Imaging

Detection of microcalcifications in mammograms using error of prediction and statistical measures
Author(s): Begoña Acha Pinero; Carmen Serrano; Rangaraj Mandayam Rangayyan; Joseph Edward Leo Desautels
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Paper Abstract

A two-stage method for detecting microcalcifications in mammograms is presented. In the first stage, the determination of the candidates for microcalcifications is performed. For this purpose, a 2-D linear prediction error filter is applied, and for those pixels where the prediction error is larger than a threshold, a statistical measure is calculated to determine whether they are candidates for microcalcifications or not. In the second stage, a feature vector is derived for each candidate, and after a classification step using a support vector machine, the final detection is performed. The algorithm is tested with 40 mammographic images, from Screen Test: The Alberta Program for the Early Detection of Breast Cancer with 50-µm resolution, and the results are evaluated using a free-response receiver operating characteristics curve. Two different analyses are performed: an individual microcalcification detection analysis and a cluster analysis. In the analysis of individual microcalcifications, detection sensitivity values of 0.75 and 0.81 are obtained at 2.6 and 6.2 false positives per image, on the average, respectively. The best performance is characterized by a sensitivity of 0.89, a specificity of 0.99, and a positive predictive value of 0.79. In cluster analysis, a sensitivity value of 0.97 is obtained at 1.77 false positives per image, and a value of 0.90 is achieved at 0.94 false positive per image.

Paper Details

Date Published: 1 January 2009
PDF: 10 pages
J. Electron. Imag. 18(1) 013011 doi: 10.1117/1.3099710
Published in: Journal of Electronic Imaging Volume 18, Issue 1
Show Author Affiliations
Begoña Acha Pinero, Escuela Superior de Ingenieros de la Univ. de Sevilla (Spain)
Carmen Serrano, Univ. de Sevilla (Spain)
Rangaraj Mandayam Rangayyan, Univ. of Calgary (Canada)
Joseph Edward Leo Desautels, Univ. of Calgary (Canada)

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