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 Wang^2
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.