该存储库包含用于连续采样的扩散 MRI 信号重建的几何深度学习 (DISCUS) 项目的代码.zip

# Welcome to DISCUS! ## Overview The Geometric Deep Learning for Diffusion MRI Signal Reconstruction with Continuous Samplings (DISCUS) method facilitates the flexible signal reconstruction for arbitrary q-vectors (query vectors) given an acquisition with an arbitrary number of measurements (observation set).  ### Usage This repository includes scripts to generate a dataset for training (`dataset.py`), to train the DISCUS method (`train.py`), and to predict diffusion MRI signals given a trained DISCUS model (`prediction.py`). A few parameters and paths have to be set in the `config.yaml` file. This file needs to be referenced with the respective function call, e.g. ``` python train.py -f config.yaml ``` <!-- start of references --> ## Reference If you use DISCUS for your research publication, please cite: _Christian Ewert*, David Kügler*, Rüdiger Stirnberg, Alexandra Koch, Anastasia Yendiki, Martin Reuter (*co-first); Geometric Deep Learning for Diffusion MRI Signal Reconstruction with Continuous Samplings (DISCUS). Imaging Neuroscience 2024; 2 1–18. doi: https://doi.org/10.1162/imag_a_00121_