Detection of masses in mammograms with adaption to breast density using genetic algorithm, phylogenetic trees, LBP and SVM

作者：

Highlights：

• Segmentation of the breast separates the skin and the background of the image is kept, with a good performance.

• High performance at the detection of the density of the breast.

• Efficient texture description method, based on the combination of Phylogenetic Trees, LBP and analysis in sub-regions.

• Adjustment of parameters according to the density classification of the breast.

摘要

•Segmentation of the breast separates the skin and the background of the image is kept, with a good performance.•High performance at the detection of the density of the breast.•Efficient texture description method, based on the combination of Phylogenetic Trees, LBP and analysis in sub-regions.•Adjustment of parameters according to the density classification of the breast.

论文关键词：Breast cancer,Computer-aided detection,Micro-genetic algorithm,Phylogenetic trees,Local binary patterns,Support vector machine

论文评审过程：Received 23 August 2014, Revised 2 July 2015, Accepted 22 July 2015, Available online 29 July 2015, Version of Record 29 August 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.07.046