AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charita…

Library for detecting lungs on chest x-ray images for further processing. It is fast and able to work on embedded devices.

Detecting tuberculosis from X-ray scan using pytorch

Deep learning model for segmentation of lung in CXR

Ensemble based transfer learning approach for accurately classifying common thoracic diseases from Chest X-Rays

CXR-ACGAN: Auxiliary Classifier GAN (AC-GAN) for Chest X-Ray (CXR) Images Generation (Pneumonia, COVID-19 and healthy patients) for the purpose of data augmentation. Implemented in TensorFlow, trained on COVIDx CXR-3 dataset.

A web app to predict whether a person has COVID-19 from their Chest X-Ray (CXR) scan by image classification using Transfer Learning with the pre-trained models VGG-16 and DenseNet201 with ImageNet weights.

Example of how to use MATLAB to produce post-hoc explanations (using Grad-CAM and image LIME) for a medical image classification task.

Implemented a CNN in Keras, that is trained on Lung Xrays to predict whether a patient has TB or not

Covid Detection from CXR Scans using Deep Multi-layered CNN

[IEEE-IRI 2023] "A Fully Connected Reproducible SE-UResNet for Multiorgan Chest Radiographs Segmentation" by Debojyoti Pal, Tanushree Meena, and Sudipta Roy.