Emory BMI GSoC Project Ideas
Niffler: A DICOM Framework for Machine Learning and Processing Pipelines.
A curated list of awesome resources, papers, datasets, and tools related to AI in radiology. This repository aims to provide a comprehensive collection of materials to facilitate research, learning, and development in the field of AI-powered radiology.
A powerful, enterprise-grade multi-agent system for advanced radiological analysis, diagnosis, and treatment planning. This system leverages specialized AI agents working in concert to provide comprehensive medical imaging analysis and care recommendations.
Deep Learning approaches in the detection of pulmonary disorders: COVID19, Tuberculosis, Bacterial, and Viral Pneumonia, Healthy/Normal using 17500 non-augmented X-ray images. 5 class classification performed using different pre-trained models like DenseNet201, Xception, Inception, and many more reaching near 99% accuracy.
Locate basic landmarks on cephalograms with AI (Pytorch)
The project is a collaboration with David Loaiza ( 4th Yr Radiologist) from Mexico at Cardiology national institute "Ignacio Chavez". The aim is to estimate the bone age from the left hand radiographs. The model will be trained on a RSNA Pediatric Bone Age Challenge (2017) public dataset and evaluated on private dataset obtained from the hospital.
A lightweight and efficient Dicom server for receiving and storing radiological images and radiation dose structured reports
Radiology Worklist & DICOM Viewer Using React TypeScript & .NET 8 core webapi using MVC Architecture and MS SQL Server
Python script for processing and visualizing DICOM medical images. Supports metadata extraction, multi-frame handling, and compressed image decompression.
Why should radiologists rely on eyesight alone, when computer vision and amazing open-source processing frameworks are already available? This respository hosts the python+webui implementation of brainstemx
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