COVID-19 discrimination framework for X-ray images by considering radiomics, selective information, feature ranking, and a novel hybrid classifier
作者:
Highlights:
• A comprehensive study presenting a novel COVID-19 framework.
• A detailed study analyzing the coronavirus vs. noncoronavirus specification.
• Assays with radiomic combinations, normalization and feature ranking methods.
• The first study using a novel optimized NN-based model on COVID-19 distinction.
摘要
•A comprehensive study presenting a novel COVID-19 framework.•A detailed study analyzing the coronavirus vs. noncoronavirus specification.•Assays with radiomic combinations, normalization and feature ranking methods.•The first study using a novel optimized NN-based model on COVID-19 distinction.
论文关键词:Binary categorization,Chaotic,Coronavirus,Framework design,Hybrid classifier,Optimization
论文评审过程:Received 5 June 2020, Revised 12 June 2021, Accepted 13 June 2021, Available online 17 June 2021, Version of Record 29 June 2021.
论文官网地址:https://doi.org/10.1016/j.image.2021.116359