deepRetinotopy

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Code for predicting retinotopy from anatomy using geometric deep learning. See paper for more --> https://www.sciencedirect.com/science/article/pii/S1053811921008971

deepRetinotopy 최신버젼 다운로드

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# DeepRetinotopy

This repository contains all source code necessary to replicate our recent work entitled "Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning" available in [NeuroImage](https://www.sciencedirect.com/science/article/pii/S1053811921008971).

## Table of Contents
* [Installation and requirements](#installation-and-requirements)
* [Manuscript](#manuscript)
* [Models](#models)
* [Retinotopy](#retinotopy)
* [Citation](#citation)
* [Contact](#contact)

## Installation and requirements

Models were generated using [Pytorch Geometric](https://pytorch-geometric.readthedocs.io/en/latest/). Since this package is under constant updates, we highly recommend that 
you follow the following steps to run our models locally:

- Create a conda environment (or docker container)
- Install torch first:
		
```bash
$ pip install torch==0.4.1    
$ pip install torchvision==0.2.1
```
	
	
- Install torch-scatter, torch-sparse, torch-cluster, torch-spline-conv and torch-geometric:

```bash
$ pip install torch-scatter==1.0.4
$ pip install torch-sparse==0.2.2
$ pip install torch-cluster==1.1.5
$ pip install torch-spline-conv==1.0.4
$ pip install torch-geometric==0.3.1
```

- Install the remaining required packages that are available at requirements.txt:

```bash
$ pip install -r requirements.txt
```   
    
- Clone DeepRetinotopy:
```bash
$ git clone git@github.com:Puckett-Lab/deepRetinotopy.git
```

Finally, install the following git repository for plots:
```bash
$ pip install git+https://github.com/felenitaribeiro/nilearn.git
```

## Manuscript

This folder contains all source code necessary to reproduce all figures and summary statistics in our manuscript.

## Models

This folder contains all source code necessary to train a new model and to generate predictions on the test dataset 
using our pre-trained models.

## Retinotopy

This folder contains all source code necessary to replicate datasets generation, in addition to functions and labels 
used for figures and models' evaluation.

## Citation

Please cite our paper if you used our model or if it was somewhat helpful for you :wink:

@article{Ribeiro2021,
		author = {Ribeiro, Fernanda L and Bollmann, Steffen and Puckett, Alexander M},
		doi = {https://doi.org/10.1016/j.neuroimage.2021.118624},
		issn = {1053-8119},
		journal = {NeuroImage},
		keywords = {cortical surface, high-resolution fMRI, machine learning, manifold, visual hierarchy,Vision},
		pages = {118624},
		title = {{Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning}},
		url = {https://www.sciencedirect.com/science/article/pii/S1053811921008971},
		year = {2021}
	}

## Contact
Fernanda Ribeiro <[fernanda.ribeiro@uq.edu.au](fernanda.ribeiro@uq.edu.au)>

Alex Puckett <[a.puckett@uq.edu.au](a.puckett@uq.edu.au)>

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