Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks
arXiv:2003.11617 · doi:10.1007/s13246-020-00865-4
Abstract
In this study, a dataset of X-Ray images from patients with common pneumonia, Covid-19, and normal incidents was utilized for the automatic detection of the Coronavirus. The aim of the study is to evaluate the performance of state-of-the-art Convolutional Neural Network architectures proposed over recent years for medical image classification. Specifically, the procedure called transfer learning was adopted. With transfer learning, the detection of various abnormalities in small medical image datasets is an achievable target, often yielding remarkable results. The dataset utilized in this experiment is a collection of 1427 X-Ray images. 224 images with confirmed Covid-19, 700 images with confirmed common pneumonia, and 504 images of normal conditions are included. The data was collected from the available X-Ray images on public medical repositories. With transfer learning, an overall accuracy of 97.82% in the detection of Covid-19 is achieved.
References in corpus (7)
- Adam: A Method for Stochastic Optimization
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- Improving neural networks by preventing co-adaptation of feature detectors
- COVID-19 Image Data Collection
- What makes ImageNet good for transfer learning?
- ImageNet Large Scale Visual Recognition Challenge
Cited by in corpus (98)
- Can AI help in screening Viral and COVID-19 pneumonia?
- Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks
- CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images
- Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
- COVID-19 Image Data Collection: Prospective Predictions Are the Future
- Improving performance of CNN to predict likelihood of COVID-19 using chest X-ray images with preprocessing algorithms
- Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts
- Extracting possibly representative COVID-19 Biomarkers from X-Ray images with Deep Learning approach and image data related to Pulmonary Diseases
- A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
- Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data
- Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
- GSA-DenseNet121-COVID-19: a Hybrid Deep Learning Architecture for the Diagnosis of COVID-19 Disease based on Gravitational Search Optimization Algorithm
- An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis
- Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks
- POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)
- Hybrid quantum convolutional neural networks model for COVID-19 prediction using chest X-Ray images
- Computer Vision For COVID-19 Control: A Survey
- Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection
- Convolutional Sparse Support Estimator Based Covid-19 Recognition from X-ray Images
- COVID-19 Infection Map Generation and Detection from Chest X-Ray Images
- Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approaches
- Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost
- Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
- Comparison of fine-tuning strategies for transfer learning in medical image classification
- A novel framework based on deep learning and ANOVA feature selection method for diagnosis of COVID-19 cases from chest X-ray Images
- Study of Different Deep Learning Approach with Explainable AI for Screening Patients with COVID-19 Symptoms: Using CT Scan and Chest X-ray Image Dataset
- OSegNet: Operational Segmentation Network for COVID-19 Detection using Chest X-ray Images
- Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19
- CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation
- Self-supervised deep convolutional neural network for chest X-ray classification
- Multi-stage transfer learning for lung segmentation using portable X-ray devices for patients with COVID-19
- An Overview on Audio, Signal, Speech, & Language Processing for COVID-19
- PDCOVIDNet: A Parallel-Dilated Convolutional Neural Network Architecture for Detecting COVID-19 from Chest X-Ray Images
- ECOVNet: An Ensemble of Deep Convolutional Neural Networks Based on EfficientNet to Detect COVID-19 From Chest X-rays
- A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
- Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A review
- Evolving Deep Convolutional Neural Network by Hybrid Sine-Cosine and Extreme Learning Machine for Real-time COVID19 Diagnosis from X-Ray Images
- COVID-19 in CXR: from Detection and Severity Scoring to Patient Disease Monitoring
- Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays Image
- Advance Warning Methodologies for COVID-19 using Chest X-Ray Images
- Robust Screening of COVID-19 from Chest X-ray via Discriminative Cost-Sensitive Learning
- Decision and Feature Level Fusion of Deep Features Extracted from Public COVID-19 Data-sets
- CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Images
- Medical Imaging and Computational Image Analysis in COVID-19 Diagnosis: A Review
- Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images
- CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
- An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
- Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation
- Detection of Covid-19 From Chest X-ray Images Using Artificial Intelligence: An Early Review
- Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Review
- Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images
- Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpus
- CVR-Net: A deep convolutional neural network for coronavirus recognition from chest radiography images
- COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images
- Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning
- COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays
- COVID-19 detection using deep convolutional neural networks and binary-differential-algorithm-based feature selection on X-ray images
- A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19
- COVIDLite: A depth-wise separable deep neural network with white balance and CLAHE for detection of COVID-19
- Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data
- Data-Driven Methods to Monitor, Model, Forecast and Control Covid-19 Pandemic: Leveraging Data Science, Epidemiology and Control Theory
- CCBlock: An Effective Use of Deep Learning for Automatic Diagnosis of COVID-19 Using X-Ray Images
- Diagnosis of COVID-19 Cases from Chest X-ray Images Using Deep Neural Network and LightGBM
- MultiFusionNet: Multilayer Multimodal Fusion of Deep Neural Networks for Chest X-Ray Image Classification
- Optimisation of non-pharmaceutical measures in COVID-19 growth via neural networks
- Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing
- Classification of COVID-19 X-ray Images Using a Combination of Deep and Handcrafted Features
- Fitness Dependent Optimizer with Neural Networks for COVID-19 patients
- Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images
- An encoder-decoder-based method for COVID-19 lung infection segmentation
- Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network
- Fuzzy Unique Image Transformation: Defense Against Adversarial Attacks On Deep COVID-19 Models
- A two-step explainable approach for COVID-19 computer-aided diagnosis from chest x-ray images
- Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation
- Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification
- Machine Learning and Deep Learning Methods for Building Intelligent Systems in Medicine and Drug Discovery: A Comprehensive Survey
- A Survey on the Use of AI and ML for Fighting the COVID-19 Pandemic
- EnD: Entangling and Disentangling deep representations for bias correction
- Randomly Initialized Convolutional Neural Network for the Recognition of COVID-19 using X-ray Images
- Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing
- Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image
- Ebola Optimization Search Algorithm (EOSA): A new metaheuristic algorithm based on the propagation model of Ebola virus disease
- Covid-19 Detection from Chest X-ray and Patient Metadata using Graph Convolutional Neural Networks
- Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection
- A free web service for fast COVID-19 classification of chest X-Ray images
- Evaluating Convolutional Neural Networks for COVID-19 classification in chest X-ray images
- Artificial Intelligence for COVID-19 Detection -- A state-of-the-art review
- ViDi: Descriptive Visual Data Clustering as Radiologist Assistant in COVID-19 Streamline Diagnostic
- Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders
- Real-time Prediction for Mechanical Ventilation in COVID-19 Patients using A Multi-task Gaussian Process Multi-objective Self-attention Network
- Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizability
- SODA: Detecting Covid-19 in Chest X-rays with Semi-supervised Open Set Domain Adaptation
- CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classification
- Survey of the Detection and Classification of Pulmonary Lesions via CT and X-Ray
- Understanding Human Innate Immune System Dependencies using Graph Neural Networks
- Characterization of Covid-19 Dataset using Complex Networks and Image Processing
- Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the System
- A Survey of Machine Learning Techniques for Detecting and Diagnosing COVID-19 from Imaging