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README

Active Contour Euler Elastica Loss Functions

Official implementations of paper: Learning Euler's Elastica Model for Medical Image Segmentation, and a short version was accepted by ISBI 2021 . * Implemented a novel active contour-based loss function, a combination of region term, length term, and elastica term (mean curvature). * Reimplemented some popular active contour-based loss functions in different ways, such as 3D Active-Contour-Loss based on Sobel filter and max-and min-pool.

Introduction and Some Results

  • Pipeline of ACE loss.

  • 2D results and visualization.

  • 3D results and visualization.

  • If you want to use these methods just as constrains (combining with dice loss or ce loss), you can use torch.mean() to replace torch.sum().

Requirements

Some important required packages include: * Pytorch version >= 0.4.1. * Python >= 3.6.

Follow official guidance to install. Pytorch.

Citation

If you find Active Contour Based Loss Functions are useful in your research, please consider to cite:

@inproceedings{chen2020aceloss,
  title={Learning Euler's Elastica Model for Medical Image Segmentation},
  author={Chen, Xu and Luo, Xiangde and Zhao, Yitian and Zhang, Shaoting and Wang, Guotai and Zheng, Yalin},
  journal={arXiv preprint arXiv:2011.00526},
  year={2020}
}

@inproceedings{chen2019learning,
  title={Learning Active Contour Models for Medical Image Segmentation},
  author={Chen, Xu and Williams, Bryan M and Vallabhaneni, Srinivasa R and Czanner, Gabriela and Williams, Rachel and Zheng, Yalin},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={11632--11640},
  year={2019}
}

Other Active Contour Based Loss Functions

  • Active Contour Loss (ACLoss).
  • Geodesic Active Contour Loss (GAC).
  • Elastic-Interaction-based Loss (EILoss)

Acknowledgement

  • We thank Dr. Jun Ma for instructive discussion of curvature implementation and also thank Mr. Yechong Huang for instructive help during the implementation processing of 3D curvature, Sobel, and Laplace operators.

Core symbols most depended-on inside this repo

ACELoss
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aceloss.py
first_derivative
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aceloss.py
second_derivative
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aceloss.py
region
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aceloss.py
elastica
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aceloss.py
first_derivative
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aceloss.py
second_derivative
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aceloss.py
region
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aceloss.py

Shape

Method 18
Class 7
Function 5

Languages

Python100%

Modules by API surface

aceloss.py30 symbols

For agents

$ claude mcp add ACELoss \
  -- python -m otcore.mcp_server <graph>

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