FractalCovNet architecture for COVID-19 Chest X-ray image Classification and CT-scan image Segmentation

2021/07/01 by Hemalatha Munusamy, Karthikeyan Jadarajan Muthukumar, Shriram Gnanaprakasam +2 · 73 citations
Computer Science · Medicine · #AI in cancer detection #Artificial intelligence #COVID-19 diagnosis using AI #Computer science #Computer vision #Coronavirus disease 2019 (COVID-19) #Medicine #Pathology #Pattern recognition (psychology) #Radiology #Radiomics and Machine Learning in Medical Imaging #Segmentation #Transfer of learning

paper · open access · doi:10.1016/j.bbe.2021.06.011

published in Journal of Applied Biomedicine 41(3), 1025-1038 (Elsevier BV)

openalex publication_date 2021/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Citations

• A new coronavirus associated with human respiratory disease in China
• Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection
• The COVID-19 vaccine development landscape
• Application of deep learning for fast detection of COVID-19 in X-Rays using nCOVnet
• PraNet: Parallel Reverse Attention Network for Polyp Segmentation
• Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection
• Coronavirus biology and replication: implications for SARS-CoV-2
• COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

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• TL-med: A Two-stage transfer learning recognition model for medical images of COVID-19
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• The internet of medical things and artificial intelligence: trends, challenges, and opportunities