Welcome to the repository for the CS771: Learning-based Computer Vision project, dedicated to comprehensive studies related to COVID-19 detection and classification using radiological methodologies. Check our final report 📜.
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COVID-19 Identification: Utilized CXRs to differentiate between COVID-19 and non-COVID-19 cases. Both positive and negative cases were confirmed using RT-PCR tests. We also published several papers in this field: Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence [https://pubs.rsna.org/doi/full/10.1148/radiol.2020202944] A Generalizable Artificial Intelligence Model for COVID-19 Classification Task Using Chest X-ray Radiographs: Evaluated Over Four Clinical Datasets with 15,097 Patients[https://arxiv.org/abs/2210.02189]
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Pneumonia Detection: Focused on pinpointing COVID-19 induced pneumonia based on annotations from radiologists, represented as bounding boxes.
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Report Turnaround Time (RTAT) Simulation: Simulated RTAT to elucidate potential advantages in streamlining patient triage.
Feedback, contributions, or questions? Don't hesitate to open an issue or propose changes through pull requests!