Classifier ensemble generation and selection with multiple feature representations for classification applications in computer-aided detection and diagnosis on mammography

作者：

Highlights：

• Novel ensemble classifier framework for improved classification of breast lesions.

• Ensemble generation algorithm using different types of breast lesion features.

• Ensemble selection mechanism to find an optimal subset of component classifiers.

• Impressive classification performance by comparing single classifier based methods.

摘要

•Novel ensemble classifier framework for improved classification of breast lesions.•Ensemble generation algorithm using different types of breast lesion features.•Ensemble selection mechanism to find an optimal subset of component classifiers.•Impressive classification performance by comparing single classifier based methods.

论文关键词：Ensemble learning,Ensemble selection,Classification,Mammographic masses,Multiple feature representations,Computer-aided Detection (CADe),Computer-aided Diagnosis (CADx)

论文评审过程：Received 25 November 2014, Revised 15 April 2015, Accepted 13 October 2015, Available online 21 October 2015, Version of Record 18 November 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.10.014