DeepCOVIDNet-CXR: deep learning strategies for identifying COVID-19 on enhanced chest X-rays.
Journal:
Biomedizinische Technik. Biomedical engineering
Published Date:
Oct 8, 2024
Abstract
OBJECTIVES: COVID-19 is one of the recent major epidemics, which accelerates its mortality and prevalence worldwide. Most literature on chest X-ray-based COVID-19 analysis has focused on multi-case classification (COVID-19, pneumonia, and normal) by the advantages of Deep Learning. However, the limited number of chest X-rays with COVID-19 is a prominent deficiency for clinical relevance. This study aims at evaluating COVID-19 identification performances using adaptive histogram equalization (AHE) to feed the ConvNet architectures with reliable lung anatomy of airways.