A novel algorithm for detection of COVID-19 by analysis of chest CT images using Hopfield neural network

作者：

Highlights：

• Presenting a new algorithm for detection of COVID-19 patients using chest CT scans.

• Hopfield neural network is used for locating the lungs and detecting the lesions.

• Using an operational research model to find the edges of the lungs.

• Presenting a new function to enhance the accuracy of finding the lesions.

• Testing 295 patients' CT images resulted in high accuracy to identify COVID-19.

摘要

•Presenting a new algorithm for detection of COVID-19 patients using chest CT scans.•Hopfield neural network is used for locating the lungs and detecting the lesions.•Using an operational research model to find the edges of the lungs.•Presenting a new function to enhance the accuracy of finding the lesions.•Testing 295 patients' CT images resulted in high accuracy to identify COVID-19.

论文关键词：COVID-19,Coronavirus disease 2019,Hopfield neural network,Image processing,Machine learning,Operation research

论文评审过程：Received 21 May 2020, Revised 30 December 2020, Accepted 22 February 2022, Available online 24 February 2022, Version of Record 2 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116740