Towards an approach using grammars for automatic classification of masses in mammograms
Author:
Affiliation:
1. Electrical Engineering, Polytechnic School University of São Paulo São Paulo Brazil
2. Information Systems, School of Arts, Sciences and Humanities University of São Paulo São Paulo Brazil
Publisher
Wiley
Subject
Artificial Intelligence,Computational Mathematics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12320
Reference36 articles.
1. Breast masses in mammography classification with local contour features
2. Texture-based features for classification of mammograms using decision tree
3. Method for breast cancer classification based solely on morphological descriptors
4. Extracting fuzzy rules for the diagnosis of breast cancer;Keleş A;Turkish J Electr Eng Comput Sci,2013
5. The power laws: Zipf and inverse Zipf for automated segmentation and classification of masses within mammograms
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1. A Stochastic Grammar Approach to Mass Classification in Mammograms;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2023-05-01
2. Breast tumor segmentation in digital mammograms using spiculated regions;Biomedical Signal Processing and Control;2022-07
3. Multi-label load disaggregation in presence of non-targeted loads;Electric Power Systems Research;2021-10
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