SUFMACS: A machine learning-based robust image segmentation framework for COVID-19 radiological image interpretation

作者：

Highlights：

• A novel superpixel and based fuzzy image segmentation method is proposed.

• This method is useful in the early screening of the COVID-19 infected patients.

• The original cuckoo search approach is modified and updated in two ways.

• A fuzzy modified objective function is proposed.

• The proposed method can be adapted for the real-life applications.

摘要

•A novel superpixel and based fuzzy image segmentation method is proposed.•This method is useful in the early screening of the COVID-19 infected patients.•The original cuckoo search approach is modified and updated in two ways.•A fuzzy modified objective function is proposed.•The proposed method can be adapted for the real-life applications.

论文关键词：COVID-19,Image segmentation,Radiological image interpretation,Machine learning,Clustering,SUFMACS

论文评审过程：Received 20 December 2020, Revised 5 March 2021, Accepted 16 April 2021, Available online 20 April 2021, Version of Record 4 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115069