In the early diagnosis of breast cancer, computer-aided diagnosis (CAD) systems help in the detection of abnormal tissue. Microcalcifications can be an early indication of breast cancer. This work describes the implementation of a new method for the detection of microcalcifications in mammographies. The images were obtained from the mini-MIAS database. In the proposed method, the images are preprocessed using an x and y gradient operators, the output of each filter is the input of a fuzzy system that will detect areas with high-tone variation. The next step consists of a cellular automaton that uses a set of local rules to eliminate noise and keep the pixels with higher probabilities of belonging to a microcalcification region. Comparative results are presented.
CITATION STYLE
Rubio, Y., Montiel, O., & Sepúlveda, R. (2017). Microcalcification detection in mammograms based on fuzzy logic and cellular automata. In Studies in Computational Intelligence (Vol. 667, pp. 583–602). Springer Verlag. https://doi.org/10.1007/978-3-319-47054-2_38
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