Skip to content
/ SPE-DNR Public

Deep-Learning Based Automated Neuron Reconstruction from 3D Microscopy Images Using Synthetic Training Images

Notifications You must be signed in to change notification settings

chwx08/SPE-DNR

Repository files navigation

Spherical-Patches-Extraction and Deep-Learning Based Neuron Reconstructor (SPE-DNR) [paper]

Introduction

The spherical-patches-extraction and deep-learning based neuron reconstructor (SPE-DNR) is an automatic method for neuron reconstruction from 3D microscopy images.

This is the source code for the SPE-DNR with pretrained weights. And here is the full supplementary material of the paper.

Requirments

  • pytorch==1.7.1
  • numpy==1.19.2
  • scipy==1.5.2
  • scikit-image==0.17.2
  • libtiff
  • tqdm

Usage

python main.py

Pretrained Weights

In folder './checkpoint/classification_checkpoints'.

Test Samples

One test image with corresponding seed maps and soma masks is in folder './test_samples'.

Citation

If the code or method help with your research, please cite the following paper:

@article{Chen2021deep,
  title={Deep-learning based automated neuron reconstruction from 3D microscopy images using synthetic training images},
  author={Chen, Weixun and Liu, Min and Du, Hao and Radojević, Miroslav and Wang, Yaonan and Meijering, Erik},
  journal={IEEE Transactions on Medical Imaging},
  year={2021},
  doi={https://doi.org/10.1109/TMI.2021.3130934}
}

About

Deep-Learning Based Automated Neuron Reconstruction from 3D Microscopy Images Using Synthetic Training Images

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages