Interval symbolic feature extraction for thermography breast cancer detection

作者：

Highlights：

• Malignant, benignant and cyst classes are classified using a symbolic feature extraction.

• Features based on interval dissimilarities are obtained from breast thermograms.

• The proposed feature extraction surpassed statistical and texture feature extractions.

• The results of performance were 85.7% of sensitivity index for the malignant class and accuracy of 84%.

摘要

•Malignant, benignant and cyst classes are classified using a symbolic feature extraction.•Features based on interval dissimilarities are obtained from breast thermograms.•The proposed feature extraction surpassed statistical and texture feature extractions.•The results of performance were 85.7% of sensitivity index for the malignant class and accuracy of 84%.

论文关键词：Thermography,SDA,Interval data,Classification

论文评审过程：Available online 9 May 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.04.027