deformation-inversion-layer

Neural network layer for inverting deformation fields

https://github.com/honkamj/deformation-inversion-layer

Science Score: 57.0%

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Repository

Neural network layer for inverting deformation fields

Basic Info

Host: GitHub
Owner: honkamj
License: mit
Language: Python
Default Branch: main
Homepage:
Size: 5.57 MB

Statistics

Stars: 11
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 5

Created almost 3 years ago · Last pushed about 1 year ago

Metadata Files

Readme License Citation

Deformation inversion layer

Deformation inversion layer is a neural network layer for inverting deformation fields develped as part of SITReg, a deep learning intra-modality image registration arhitecture fulfilling strict symmetry properties.

example of an inverted deformation

Installation

Install using pip by running the command

pip install deformation-inversion-layer

Requirements

Python 3.8+
PyTorch 1.10+

Documentation

For a quick start tutorial, see quick_start.ipynb. For API reference, go to https://honkamj.github.io/deformation-inversion-layer/.

SITReg

For SITReg implementation, see repository SITReg.

Publication

If you use deformation inversion layer, or other parts of the repository, please cite (see bibtex):

SITReg: Multi-resolution architecture for symmetric, inverse consistent, and topology preserving image registration
Joel Honkamaa, Pekka Marttinen
The Journal of Machine Learning for Biomedical Imaging (MELBA) (10.59275/j.melba.2024-276b)

Acknowledgments

Tutorial by Zico Kolter, David Duvenaud, and Matt Johnson was very helpful in implementing the layer.

License

Deformation inversion layer and SITReg are released under the MIT license.

Owner

Name: Joel Honkamaa
Login: honkamj
Kind: user
Location: Finland
Company: Aalto University

Repositories: 1
Profile: https://github.com/honkamj

AI researcher at Aalto University, Finland

Citation (citations.bib)

@article{melba:2024:026:honkamaa,
    title = "SITReg: Multi-resolution architecture for symmetric, inverse consistent, and topology preserving image registration",
    author = "Honkamaa, Joel and Marttinen, Pekka",
    journal = "Machine Learning for Biomedical Imaging",
    volume = "2",
    issue = "November 2024 issue",
    year = "2024",
    pages = "2148--2194",
    issn = "2766-905X",
    doi = "https://doi.org/10.59275/j.melba.2024-276b",
    url = "https://melba-journal.org/2024:026"
}

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Total packages: 1
Total downloads:
- pypi 60 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 4
Total maintainers: 1

pypi.org: deformation-inversion-layer

Deformation inversion layer is a neural network layer for inverting deformation fields

Homepage: https://github.com/honkamj/deformation-inversion-layer
Documentation: https://deformation-inversion-layer.readthedocs.io/
License: MIT License Copyright (c) 2023 Joel Honkamaa Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Latest release: 1.1.2
published about 2 years ago

Versions: 4
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 60 Last month

Rankings

Dependent packages count: 7.3%

Average: 29.6%

Forks count: 30.5%

Stargazers count: 39.4%

Dependent repos count: 41.4%

Maintainers (1)

honkamj