Improved method for detection of microcalcification clusters in digital mammograms

Wouter J. H. Veldkamp; Nico Karssemeijer

doi:10.1117/12.348607

21 May 1999 Improved method for detection of microcalcification clusters in digital mammograms

Wouter J. H. Veldkamp, Nico Karssemeijer

Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999) https://doi.org/10.1117/12.348607
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

In this study it is shown that the performance of a statistical method for detection of microcalcification clusters in digital mammograms, can be improved substantially by using a second step of classification. During this second step, detected clusters are automatically classified into true positive and false positive detected clusters. For classification the k-nearest neighbor method was used in a leave-one-patient-out procedure. The sensitivity level of the method was adjusted both in the first detection step as in the second classification step. The Mahalanobis distance was used as criterion in the sequential forward selection procedure for selection of features. This primary feature selection method was combined with a classification performance criterion for the final feature selection. By applying the initial detection at various levels of sensitivity, various sets of false and true positive detected clusters were created. At each of these sets the classification ca be performed. Results show that the overall best FROC performance after secondary classification is obtained by varying sensitivity levels in both the first and second step. Furthermore, it was shown that performing a new feature selection for each different set of false and true positives is essential. A large database of 245 digitized mammograms with 341 clusters was used for evaluation of the method.

Citation Download Citation

Wouter J. H. Veldkamp and Nico Karssemeijer "Improved method for detection of microcalcification clusters in digital mammograms", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348607

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