A New Mammography Image Classification System by Deep Learning and Feature Selection

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Volume 4, Issue 12 (December, 2018)
Publication No:
Baljeet Kumar, Sumit Chopra
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The classification of breast masses from mammograms into benign or malignant has been commonly addressed with machine learning classifiers that use as input a large set of hand-crafted features, usually based on general geometrical and texture information. In this paper, we propose a novel deep learning method that automatically learns features based directly on the optimization of breast mass classification from mammograms, where we target an improved classification performance compared to the approach described above. The novelty of our approach lies in two step features optimization particle swarm optimization (PSO) and learning with convolution neural network (CNN).In proposed approach improve by accuracy 98.45%.

PSO, CNN, optimization, texture features