COVID 19 Detection Flask App Based On Chest X Rays And CT Scans
COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU...
Overview:
The COVID-19 Detection Flask App is a project that focuses on detecting COVID-19 based on Chest X-rays and CT Scans using four Transfer Learning algorithms. The trained models offer accuracies for predicting the possibility of a COVID infection to users who upload their medical images to the Flask App.
Features:
- Transfer Learning Algorithms: Utilizes VGG16, ResNet50, InceptionV3, and Xception.
- Live Demo: Users can test the detection capabilities of the app.
- Dataset Collection: Utilizes datasets of Chest X-ray and CT Scan images from various sources.
- Technical Concepts Explanation: Offers insights into concepts like ImageNet, ResNet50, VGG16, and Inception-V3.
Summary:
The COVID-19 Detection Flask App is a project that leverages deep learning and transfer learning algorithms to detect COVID-19 based on medical images. With a focus on user-friendliness and accuracy, the app provides a valuable tool for individuals and healthcare professionals to assess the possibility of COVID-19 infection based on Chest X-ray and CT Scan images.