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radiography

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[IEEE TPAMI 2024] SimSID: unsupervised anomaly detection in chest radiography. SimSID learns the recurrent anatomical patterns of normal chest X-rays and flags deviations, using no anomaly labels in training. +8.0% / +5.0% / +9.9% AUC over prior state of the art on ZhangLab, COVIDx and CheXpert. TPAMI extension of SQUID (CVPR 2023).

  • Updated Sep 9, 2026
  • Python
Radiography-Based-Diagnosis-Of-COVID-19-Using-Deep-Learning

Developed a Convolutional Neural Network based on VGG16 architecture to diagnose COVID-19 and classify chest X-rays of patients suffering from COVID-19, Ground Glass Opacity and Viral Pneumonia. This repository contains the link to the dataset, python code for visualizing the obtained data and developing the model using Keras API.

  • Updated Apr 15, 2021
  • Jupyter Notebook

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