UMIS

Official PyTorch implementation of "Unsupervised Microvascular Image Segmentation Using an Active Contours Mimicking Neural Network" (link)

Prerequisites

• Python 3.6
• Pytorch +1.4
• Numpy
• Scipy
• OpenCV
• Path
• tqdm
• h5py
• tifffile
• libtiff

Morphological Pooling Layer

In order to build the Morphological Pooling layer on your own machine, run the following line

python src/setup.py install

Train

You can now train using the Euler-Lagrange (original paper), or the PDE (level-set) loss with additional regularization for stability.

python train_unsup.py --loss <EL/LS>

Citation

@inproceedings{gur2019unsupervised,
  title={Unsupervised Microvascular Image Segmentation Using an Active Contours Mimicking Neural Network},
  author={Gur, Shir and Wolf, Lior and Golgher, Lior and Blinder, Pablo},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={10722--10731},
  year={2019}
}