Title
Microcalcifications detection in mammograms based on Ant Colony Optimization and Markov Random Field
Abstract
Mammography constitutes a credible technique for the detection of breast cancer. Early detection of microcalcifications in breast tissue, which is an indication of developing breast cancer, facilitates prompt intervention averting fatalities associated with this type of disease. It is, however, difficult for practitioners to pinpoint effectively the affected regions of the breast. This paper proposes a novel method for microcalcifications detection based on a hybrid metaheuristic approach using Ant Colony Optimization and Markov Random Field approaches. Markov Random Fields are used to model spatial relation between different neighboring pixels via an energy function. This energy function is then optimized using an Ant colony so to find its minimum value. The proposed algorithm is tested on the mini-MIAS mammogram database. The obtained results, evaluated using Borsotti criterion, show the good accuracy and efficiency of our approach.
Year
DOI
Venue
2014
10.1109/SOCPAR.2014.7008004
Soft Computing and Pattern Recognition
Keywords
Field
DocType
Markov processes,ant colony optimisation,cancer,mammography,medical image processing,Borsotti criterion,Markov random field approach,ant colony optimization,breast cancer detection,breast tissue,energy function,hybrid metaheuristic approach,mammography,microcalcification detection,mini-MIAS mammogram database,neighboring pixels,spatial relation,Ant Colony Optimization,Breast cancer,Computer Aided Detection,Mammography,Markov Random Fields,Microcalcification,Regions Of Interest,Segmentation
Ant colony optimization algorithms,Mammography,Random field,Pattern recognition,Computer science,Markov random field,Markov chain,Image segmentation,Artificial intelligence,Ant colony,Machine learning,Metaheuristic
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
4
Name
Order
Citations
PageRank
Amira Bacha100.34
Karim Kalti2208.58
Ben Amara, N.E.3375.45
Basel Solaiman412735.05