An automatic BI-RADS description of mammographic masses by fusing multiresolution features
作者：
Highlights：
• An automatic method that performs a BI-RADS description of mammographic masses.
• A multiple kernel learning strategy is proposed for combining two multiresolution features.
• Mass shape description is assigned by a hierarchical SVM classifier.
• The margin and density descriptions are assigned by a shape-based retrieval strategy.
• The method was evaluated on the datasets: DDSM and INBreast.
摘要
•An automatic method that performs a BI-RADS description of mammographic masses.•A multiple kernel learning strategy is proposed for combining two multiresolution features.•Mass shape description is assigned by a hierarchical SVM classifier.•The margin and density descriptions are assigned by a shape-based retrieval strategy.•The method was evaluated on the datasets: DDSM and INBreast.
论文关键词：BI-RADS mammographic lexicon,Mammographic mass description,Zernike moments,Curvelet transform,Multiple kernel learning
论文评审过程：Received 24 June 2016, Revised 14 November 2016, Accepted 20 November 2016, Available online 21 December 2016, Version of Record 17 January 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.11.031
