# COVID-19 Image Data Collection

arXiv: https://arxiv.org/abs/2003.11597 · HTML: https://mlsanity.com/paper/2003.11597/

## Key facts

- Cited by 101 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Mar 2020.

## Built on by (most cited first, 30 of 101)

- [SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks](https://mlsanity.com/paper/2311.11969/) (2023)
- [Concept-level Debugging of Part-Prototype Networks](https://mlsanity.com/paper/2205.15769/) (2022)
- [FLOP: Federated Learning on Medical Datasets using Partial Networks](https://mlsanity.com/paper/2102.05218/) (2021)
- [Transformers in Medical Image Analysis: A Review](https://mlsanity.com/paper/2202.12165/) (2022)
- [The Clever Hans Mirage: A Comprehensive Survey on Spurious Correlations in Machine Learning](https://mlsanity.com/paper/2402.12715/) (2024)
- [Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models](https://mlsanity.com/paper/2310.03182/) (2023)
- [QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Training](https://mlsanity.com/paper/2506.00711/) (2025)
- [Explainable Deep Learning Methods in Medical Image Classification: A Survey](https://mlsanity.com/paper/2205.04766/) (2022)
- [Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network](https://mlsanity.com/paper/2302.09814/) (2023)
- [Improving deep neural network generalization and robustness to background bias via layer-wise relevance propagation optimization](https://mlsanity.com/paper/2202.00232/) (2022)
- [Automated Generation of Accurate & Fluent Medical X-ray Reports](https://mlsanity.com/paper/2108.12126/) (2021)
- [FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia](https://mlsanity.com/paper/2104.12581/) (2021)
- [COVID-Net CXR-2: An Enhanced Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-ray Images](https://mlsanity.com/paper/2105.06640/) (2021)
- [Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports](https://mlsanity.com/paper/2110.03094/) (2021)
- [Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlooks](https://mlsanity.com/paper/2410.02331/) (2024)
- [A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industry](https://mlsanity.com/paper/2404.15777/) (2024)
- [MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generation](https://mlsanity.com/paper/2409.19684/) (2024)
- [A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis](https://mlsanity.com/paper/2405.14839/) (2024)
- [Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans](https://mlsanity.com/paper/2101.05442/) (2021)
- [A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron](https://mlsanity.com/paper/2202.06372/) (2022)
- [Image Data collection and implementation of deep learning-based model in detecting Monkeypox disease using modified VGG16](https://mlsanity.com/paper/2206.01862/) (2022)
- [CLIMB: Data Foundations for Large Scale Multimodal Clinical Foundation Models](https://mlsanity.com/paper/2503.07667/) (2025)
- [A foundation model for generalizable disease diagnosis in chest X-ray images](https://mlsanity.com/paper/2410.08861/) (2024)
- [COVIDx CXR-3: A Large-Scale, Open-Source Benchmark Dataset of Chest X-ray Images for Computer-Aided COVID-19 Diagnostics](https://mlsanity.com/paper/2206.03671/) (2022)
- [A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions](https://mlsanity.com/paper/2406.03820/) (2024)
- [Recent Progress in Transformer-based Medical Image Analysis](https://mlsanity.com/paper/2208.06643/) (2022)
- [COVID-19 detection from scarce chest x-ray image data using few-shot deep learning approach](https://mlsanity.com/paper/2102.06285/) (2021)
- [Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost](https://mlsanity.com/paper/2109.02428/) (2021)
- [Inverse Problems Leveraging Pre-trained Contrastive Representations](https://mlsanity.com/paper/2110.07439/) (2021)
- [On Calibrated Model Uncertainty in Deep Learning](https://mlsanity.com/paper/2206.07795/) (2022)

## Abstract (arXiv)

This paper describes the initial COVID-19 open image data collection. It was created by assembling medical images from websites and publications and currently contains 123 frontal view X-rays.