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This repository contains prototype scripts for GDSC NU Angio application

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ARCADE - Automatic Region-based Coronary Artery Disease Diagnostics using x-ray angiography imagEs

GDSC Solution Challenge Logo

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Demo: YouTube

About the project

Coronary artery disease (CAD) is a condition caused by the buildup of atherosclerotic plaques inside coronary arteries, which can lead to a reduction in blood supply to the heart. It is one of the leading causes of death worldwide. The most common diagnostic procedure for CAD is coronary angiography, which uses contrast material and X-rays to observe lesions in the arteries in real-time, allowing for precise detection of stenosis and control of intraventricular interventions and stent insertions. This procedure is useful for planning necessary revascularization procedures based on the calculated occlusion and affected segment of coronary arteries.

With this project, we aim to provide an automated diagnostics tool that is able to provide a timely recommendation on whether intervention is required or not using deep-learning algorithms.

Dataset

Dataset will be published with MICCAI2023 ARCADE challenge

Tech Stack

  • Python (Tensorflow, Keras, OpenCV)
  • Golang
  • Angular.js
  • Google Compute Engine

Authors

  • Beknur Raissov
  • Maxim Popov
  • Nuren Zhaksylyk

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This repository contains prototype scripts for GDSC NU Angio application

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  • HTML 1.3%