[IEEE-IRI 2023] "A Fully Connected Reproducible SE-UResNet for Multiorgan Chest Radiographs Segmentation" by Debojyoti Pal, Tanushree Meena, and Sudipta Roy.
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Sep 4, 2023 - Jupyter Notebook
[IEEE-IRI 2023] "A Fully Connected Reproducible SE-UResNet for Multiorgan Chest Radiographs Segmentation" by Debojyoti Pal, Tanushree Meena, and Sudipta Roy.
Covid Detection from CXR Scans using Deep Multi-layered CNN
Implemented a CNN in Keras, that is trained on Lung Xrays to predict whether a patient has TB or not
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.
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.
Deep learning model for segmentation of lung in CXR
Ensemble based transfer learning approach for accurately classifying common thoracic diseases from Chest X-Rays
Detecting tuberculosis from X-ray scan using pytorch
Library for detecting lungs on chest x-ray images for further processing. It is fast and able to work on embedded devices.
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…
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