Detecting tuberculosis from X-ray scan using pytorch
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Updated
Jan 23, 2019 - Jupyter Notebook
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…
Deep learning model for segmentation of lung in CXR
Covid Detection from CXR Scans using Deep Multi-layered CNN
Ensemble based transfer learning approach for accurately classifying common thoracic diseases from Chest X-Rays
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
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.
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.
[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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