Thyroid lesion classification in 242 patient population using Gabor transform features from high resolution ultrasound images
作者：
Highlights：
• Total of 242 benign and malignant thyroid nodules are classified.
• Various entropies are extracted from Gabor transformed images.
• These features are subjected to LSDA and ranked by Relief-F method.
• Various sampling strategies are used to balance the classification data.
• Obtained classification accuracy of 94.3% with C4.5 decision tree classifier.
摘要
•Total of 242 benign and malignant thyroid nodules are classified.•Various entropies are extracted from Gabor transformed images.•These features are subjected to LSDA and ranked by Relief-F method.•Various sampling strategies are used to balance the classification data.•Obtained classification accuracy of 94.3% with C4.5 decision tree classifier.
论文关键词：Thyroid nodules,High resolution,SMOTE,Over-sampling strategies,Post hoc test,Relief-F,LSDA
论文评审过程：Received 9 February 2016, Revised 10 May 2016, Accepted 10 June 2016, Available online 11 June 2016, Version of Record 9 July 2016.
论文官网地址：https://doi.org/10.1016/j.knosys.2016.06.010
