Abstract
We describe a new algorithm for microcalcification segmentation in mammographic X-ray images. The algorithm detects microcalcifications in two steps. First, it removes background tissue with a multiscale morphological operation. Then, it applies entropy thresholding based on a 3-dimensional co-occurrence matrix. Unlike existing methods, ours is fully automatic, parameter-free, and independent of local statistics. To test its efficacy, we applied it to images from the Mammographic Image Analysis Society database and analyzed the results with the assistance of a clinician. We obtained detection rates of 93.75% of true positives, 6.25% of false positives, and 2% of false negatives.
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References
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Melloul, M., Joskowicz, L. (2002). Segmentation of microcalcification in X-ray mammograms using entropy thresholding. In: Lemke, H.U., Inamura, K., Doi, K., Vannier, M.W., Farman, A.G., Reiber, J.H.C. (eds) CARS 2002 Computer Assisted Radiology and Surgery. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56168-9_112
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DOI: https://doi.org/10.1007/978-3-642-56168-9_112
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