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https://github.com/bowang-lab/maester

Masked Autoencoder Guided Segmentation at Pixel Resolution

https://github.com/bowang-lab/maester

Science Score: 36.0%

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Last synced: 10 months ago · JSON representation

Repository

Masked Autoencoder Guided Segmentation at Pixel Resolution

Basic Info
  • Host: GitHub
  • Owner: bowang-lab
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 1.39 MB
Statistics
  • Stars: 15
  • Watchers: 4
  • Forks: 6
  • Open Issues: 2
  • Releases: 0
Created over 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License

README.md

CVPR2023 Highlight | MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition

Check out the Paper! and our Youtube Talk!

💥 Introduction

We introduce MAESTER (Masked AutoEncoder guided SegmenTation at pixEl Resolution), a self-supervised method for accurate, subcellular structure segmentation at pixel resolution. MAESTER treats volume electron microscopy(vEM) image segmentation as a representation learning and clustering problem. Specifically, MAESTER learns semantically meaningful token representations of multi-pixel image patches while simultaneously maintaining a sufficiently large field of view for contextual learning. We also develop a cover-and-stride inference strategy to achieve pixel-level subcellular strueture segmentation.

⚙️ Installation

  • Clone the repository:

git clone https://github.com/bowang-lab/MAESTER

  • Set up the environment:

poetry install poetry shell pip install torch==2.0.1 torchvision==0.15.2

  • Download the trained model for demo

    • Google drive: https://drive.google.com/drive/folders/143W_VSl5ONE3NGbnI0i19S8lBRml7lRz?usp=sharing
    • Put it under ./MAESTER/model_weights/

  • Dataset:

wget https://cloud.mpi-cbg.de/index.php/s/UJopHTRuh6f4wR8/download

  • and unzip the dataset, put it under ./MAESTER/data/

🎉 Example

  • Check out our detailed demo:
    • Inference with MAESTER ./examples/inference_demo.ipynb.

📝 To-do

  • [x] Add inference demo
  • [ ] Add scalable inference example
  • [ ] Add DDP training example

📄 Citation

@InProceedings{Xie_2023_CVPR, author = {Xie, Ronald and Pang, Kuan and Bader, Gary D. and Wang, Bo}, title = {MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2023}, pages = {3292-3301} }

Acknowledgement

  • This repository is built upon MAE.

Owner

  • Name: WangLab @ U of T
  • Login: bowang-lab
  • Kind: organization
  • Location: 190 Elizabeth St, Toronto, ON M5G 2C4 Canada

BoWang's Lab at University of Toronto

GitHub Events

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Ronald Xie 4****n 1
Kuan-Pang k****g@m****a 1
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mail.utoronto.ca: 1

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  • AlexSauer (1)
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  • mese79 (1)
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