@inbook{a0fa6a1e41d242f886564d77e4a3b68c,
title = "Microcalcification detection in mammograms based on fuzzy logic and cellular automata",
abstract = "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.",
keywords = "Breast cancer, Cellular automata, Fuzzy system, Mammography image image enhancement, Microcalcification",
author = "Yoshio Rubio and Oscar Montiel and Roberto Sep{\'u}lveda",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.",
year = "2017",
doi = "10.1007/978-3-319-47054-2_38",
language = "Ingl{\'e}s",
series = "Studies in Computational Intelligence",
publisher = "Springer Verlag",
pages = "583--602",
booktitle = "Studies in Computational Intelligence",
address = "Alemania",
}
