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locor

Locor is a generic multimodal image registration tool based on modeling local functional dependence with linear combination of learned basis functions.

https://github.com/honkamj/locor

Science Score: 54.0%

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    Links to: arxiv.org
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    Low similarity (9.4%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Locor is a generic multimodal image registration tool based on modeling local functional dependence with linear combination of learned basis functions.

Basic Info
  • Host: GitHub
  • Owner: honkamj
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 124 KB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed 9 months ago
Metadata Files
Readme License Citation

README.md

Locor

Locor is a generic multimodal image registration tool based on modaling local functional dependence with linear combination of learned basis functions.

Installation

First, install PyTorch with instructions at https://pytorch.org/ (GPU version highly recommended).

Then you can install Locor using pip by running the command

pip install git+https://github.com/honkamj/locor

Usage

The registration is invoked via running python -m locor. The most basic use case is:

python -m locor <path_to_the_reference_image> <path_to_the_moving_image> -o <path_to_the_registered_moving_image.nii>

The images should be readable by nibabel (https://nipy.org/nibabel/). To see all the available options, run python -m locor -h.

Custom config files can be given with flag "-c". For Locor config files are defined as Python scripts defining a method "build_config". See the default config for an example.

Publication

If you use the method, please cite (see bibtex):

  • New multimodal similarity measure for image registration via modeling local functional dependence with linear combination of learned basis functions
    Joel Honkamaa, Pekka Marttinen
    Under review (eprint arXiv:2503.05335)

License

Locor tool is released under the MIT license.

Owner

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

AI researcher at Aalto University, Finland

Citation (citations.bib) 

@article{honkamaa2025locor,
  title={New multimodal similarity measure for image registration via modeling local functional dependence with linear combination of learned basis functions},
  author={Honkamaa, Joel and Marttinen, Pekka},
  journal={arXiv preprint arXiv:2503.05335},
  year={2025}
}

GitHub Events

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Dependencies

environment.yml conda
  • black
  • ipykernel
  • isort
  • matplotlib
  • mypy
  • pip
  • pylint
  • python 3.10.*
  • pytorch 2.5.*
  • pytorch-cuda 11.8.*
  • torchaudio
  • torchvision
  • tqdm
  • twine
pyproject.toml pypi
  • nibabel *
  • numpy *
  • torch >=2.0
  • tqdm *
setup.py pypi