Abstract
In this work, a detection scheme for microcalcifications is presented. Candidate microcalcifications are detected using non-linear filtering. In order to improve the performance, we investigate the use of an additional classification step. Two types of local texture-based features are defined. The advantage compared to region-based feature sets is elaborated. Classification is performed using feedforward neural networks.
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© 1998 Springer Science+Business Media Dordrecht
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Meersman, D., Scheunders, P., Van Dyck, D. (1998). Classification of Microcalcifications Using Texture-Based Features. In: Karssemeijer, N., Thijssen, M., Hendriks, J., van Erning, L. (eds) Digital Mammography. Computational Imaging and Vision, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5318-8_38
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DOI: https://doi.org/10.1007/978-94-011-5318-8_38
Publisher Name: Springer, Dordrecht
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