Popular GitHub Repositories for Cxr Lungs

TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

Improving Chest X-Ray Report Generation by Leveraging Warm-Starting

The code to finetune SAM with bounding box prompt for segmentation of the lungs on CT

Repository processes CT scanned images of human Lungs , which are in DICOM image format. Visualises the data in 3D and trains a 3D convolution network on the data after preprocessing.

Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)

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.

Securing Collaborative Medical AI by Using Differential Privacy

An end to end automatic segmentation tool for MRI files, that can identify lungs, bladder, liver, kidney and bone

Embeddings generation from MIMIC-IV and MIMIC-CXR

COVID-19 Detection Using CXR and Attention Guided CNN

This repository contains the image classification followed by semantic segmentation of Chest X-Rays to detect a clinical condition called Pneumothorax.

Machine Learning 2 Course Project at RKMVERI, 2021. Published at The Imaging Science Journal (2023), Paper: https://www.tandfonline.com/doi/full/10.1080/13682199.2023.2174657

Repository for the journal article, 'Federated Semi-Supervised Multi-Task Learning to Detect COVID-19 and Lungs Segmentation Marking Using Chest Radiography Images and Raspberry Pi Devices: An Internet of Medical Things Application', Mahbub Ul Alam, Rahim Rahmani. Sensors 21, no. 15: 5025, https://doi.org/10.3390/s21155025.

ChestXLLaMA is a multimodal LLM for chest X-ray report generation. It builds on LLaMA-3.2 Vision with: Large-scale training on MIMIC-CXR + CheXpert Plus 10-step reasoning distillation for transparent clinical logic Efficient 4-bit deployment (Unsloth + bitsandbytes) ⚠️ Research/educational use only — not for autonomous clinical decisions.

Mini CLIP-style CXR↔report retrieval with prompt ablation, token-length check, and interpretability

Interactive visualization of Emory CXR embeddings using foundation models for subgroup analysis.

RadLLaMA-Thinking is a multimodal LLM for chest X-ray report generation. It builds on LLaMA-3.2 Vision with: Large-scale training on MIMIC-CXR + CheXpert Plus 10-step reasoning distillation for transparent clinical logic Efficient 4-bit deployment (Unsloth + bitsandbytes) ⚠️ Research/educational use only — not for autonomous clinical decisions.