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Voxel2Hemodynamics

Introduction

This is the repo of the STACOM2023 paper Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics. End to End Hemodynamic Prediction Framework

Content

This repo contains an end to end framework to get the hemodynamics prediction of coronary artery given a dcm image. First we generate pointcloud data from dcm and then use pointnet++ to predict the hemodynamics. Here are only part of the code for the paper and this repo is still being updated.

Setup

cd Voxel2Hemodynamics
pip install -r requirement.txt

Directory Structure

Voxel2Hemodynamic
├── checkpoints (please download the weight and create this directory yourself)
├── data
    ├── test_data
├── data_utils
├── README.md
├── models
    ├── pointnet2_sem_seg.py(point cloud module)
├── DDP_test.sh
├── config-predict.yaml
└── mtools(segmentation and vectorization module)

Visualization

After the prediction, the visualization result of the prediction can be get using the software Paraview the link for download this software is: https://www.paraview.org/