Ambiguous D-means fusion clustering algorithm based on ambiguous set theory: Special application in clustering of CT scan images of COVID-19

作者：

Highlights：

• This paper discusses a new ambiguous set theory.

• For the theory, various mathematical formulas and definitions are discussed.

• Based on ambiguous set, entropy and image fusion concepts, a new image clustering algorithm is proposed.

• The algorithm’s application is shown in chest CT scan images of COVID-19 patients.

• Performance evaluation metrics indicate the efficacy of the proposed algorithm.

摘要

•This paper discusses a new ambiguous set theory.•For the theory, various mathematical formulas and definitions are discussed.•Based on ambiguous set, entropy and image fusion concepts, a new image clustering algorithm is proposed.•The algorithm’s application is shown in chest CT scan images of COVID-19 patients.•Performance evaluation metrics indicate the efficacy of the proposed algorithm.

论文关键词：Coronavirus disease 2019 (COVID-19),Computed tomography (CT),Ambiguous set theory,Ambiguous D-means fusion clustering algorithm (ADMFCA),Clustering

论文评审过程：Received 3 April 2021, Revised 17 August 2021, Accepted 20 August 2021, Available online 26 August 2021, Version of Record 1 September 2021.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.107432