Pyramid Transformer Net (PTNet)
Project | Paper
Pytorch implementation of PTNet for high-resolution and longitudinal infant MRI synthesis.
PTNet: A High-Resolution Infant MRI Synthesizer Based on Transformer
Xuzhe Zhang1, Xinzi He1, Jia Guo2, Nabil Ettehadi1, Natalie Aw2, David Semanek2, Jonathan Posner2, Andrew Laine1, Yun Wang2
1Columbia University Department of Biomedical Engineering, 2CUMC Department of Psychiatry
Usage and Demo
Coming Soon
Prerequisites
- Linux
- Python3.6
- NVIDIA GPU (11G memory or larger) + CUDA cuDNN
Getting Started
Installation
coming soon
Testing
coming soon
Dataset
coming soon
Training
coming soon
More Training/Test Details
coming soon
Citation
If you find this useful for your research, please use the following.
@article{zhang2021ptnet,
title={PTNet: A High-Resolution Infant MRI Synthesizer Based on Transformer},
author={Zhang, Xuzhe and He, Xinzi and Guo, Jia and Ettehadi, Nabil and Aw, Natalie and Semanek, David and Posner, Jonathan and Laine, Andrew and Wang, Yun},
journal={arXiv preprint arXiv:2105.13993},
year={2021}
}
Acknowledgments
This code borrows heavily from: Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, pix2pixHD, pytorch-CycleGAN-and-pix2pix.