ReviewComputer methods and programs in biomedicine update2022
A COMPARATIVE STUDY OF X-RAY AND CT IMAGES IN COVID-19 DETECTION USING IMAGE PROCESSING AND DEEP LEARNING TECHNIQUES.
Review in Computer methods and programs in biomedicine update, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Viral pneumonia detection during the COVID-19 pandemic using deep learning and DCGAN-based data augmentation.Scientific reports · 2026Article
- Classification of the ICU Admission for COVID-19 Patients with Transfer Learning Models Using Chest X-Ray Images.Diagnostics (Basel, Switzerland) · 2025Article
- Facial Recognition Algorithms: A Systematic Literature Review.Journal of imaging · 2025Review
- A comparative analysis of the binary and multiclass classified chest X-ray images of pneumonia and COVID-19 with ML and DL models.Open medicine (Warsaw, Poland) · 2025Article
- Novel Hybrid Quantum Architecture-Based Lung Cancer Detection Using Chest Radiograph and Computerized Tomography Images.Bioengineering (Basel, Switzerland) · 2024Article
- BézierCE: Low-Light Image Enhancement via Zero-Reference Bézier Curve Estimation.Sensors (Basel, Switzerland) · 2023Article
- [A semi-supervised network-based tissue-aware contrast enhancement method for CT images].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
- A Novel Deep Learning-Based Classification Framework for COVID-19 Assisted with Weighted Average Ensemble Modeling.Diagnostics (Basel, Switzerland) · 2023Article
- A Review of Recent Advances in Deep Learning Models for Chest Disease Detection Using Radiography.Diagnostics (Basel, Switzerland) · 2023Review
- Machine Learning and COVID-19: Lessons from SARS-CoV-2.Advances in experimental medicine and biology · 2023Article
- A review on lung disease recognition by acoustic signal analysis with deep learning networks.Journal of big data · 2023Article
- Combined Cloud-Based Inference System for the Classification of COVID-19 in CT-Scan and X-Ray Images.New generation computing · 2023Article
- Preliminary Stages for COVID-19 Detection Using Image Processing.Diagnostics (Basel, Switzerland) · 2022Review
- A Deep Learning Approach for the Morphological Recognition of Reactive Lymphocytes in Patients with COVID-19 Infection.Bioengineering (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
The deadly coronavirus has not just devastated the lives of millions but has put the entire healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a significant role in isolating the positive cases and preventing the further spread of the disease. The medical images along with deep learning models provided faster and more accurate results in the detection of COVID-19. This article extensively reviews the recent deep learning techniques for COVID-19 diagnosis. The research articles discussed reveal that Convolutional Neural Network (CNN) is the most popular deep learning algorithm in detecting COVID-19 from medical images. An overview of the necessity of pre-processing the medical images, transfer learning and data augmentation techniques to deal with data scarcity problems, use of pre-trained models to save time and the role of medical images in the automatic detection of COVID-19 are summarized. This article also provides a sensible outlook for the young researchers to develop highly effective CNN models coupled with medical images in the early detection of the disease.
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