Classification of Microcalcifications Using Texture-Based Features

Author:

Meersman Dirk,Scheunders Paul,Van Dyck Dirk

Publisher

Springer Netherlands

Reference9 articles.

1. Chitre Y, Dhawan AP, Moskowitz M (1994) Artificial neural network based classification of mammographic microcalcifications using image structure features, in KW Boyer et al (eds), State of the art in digital mammographic image analysis, World Scientific, Singapore

2. Haralick RM, Shawmugan K (1973) Texture features for image classification, IEEE transactions on Systems, Man and Cybernetics, 3, pp 610–621.

3. Hojjatoleslami SA, Kittler J (1996) Detection of clusters of microcalcifications using a K-nearest neighbor rule with locally optimum distance metric, In: K Doi et al (eds.), Digital Mammography’ 96, Elsevier, Amsterdam, pp 267–272.

4. Karssemeijer N (1993) Adaptive noise equalisation and recognition of microcalcifications in mammograms, International Journal of Pattern Recognition and Artificial Intelligence, 7, pp 1357–1376.

5. “Images were provided by courtesy of the National Expert and Training Centre for Breast Cancer Screening and the Department of Radiology at the University of Nijmegen, the Netherlands,” available by ftp at ftp://marathon.csee.usf.edu .

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