Metadata-Version: 2.1
Name: patch-denoise
Version: 1.3.2
Summary: Denoising method for sequence of images or volumes. Primarly targeting fMRI data.
Author-email: Pierre-antoine Comby <pierre-antoine.comby@crans.org>
License: MIT License
        
        Copyright (c) 2023 Pierre-Antoine Comby
        
        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.
        
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Image Processing
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.8
Description-Content-Type: text/x-rst
Provides-Extra: optional
Provides-Extra: test
Provides-Extra: doc
Provides-Extra: dev
License-File: LICENSE.txt

========================
Patch Denoising Methods
========================


|COVERAGE| |CI| |CD| 
|DOC| |RELEASE|  |PYVERSION|

|LINTER| |STYLE| |LICENSE| |CITATION|


.. |COVERAGE| image:: https://img.shields.io/codecov/c/github/paquiteau/patch-denoising
   :target: https://app.codecov.io/gh/paquiteau/patch-denoising
.. |CI| image:: https://github.com/paquiteau/patch-denoising/workflows/CI/badge.svg
.. |CD| image:: https://github.com/paquiteau/patch-denoising/workflows/CD/badge.svg
.. |LICENSE| image:: https://img.shields.io/github/license/paquiteau/patch-denoising
.. |DOC| image:: https://img.shields.io/badge/docs-Sphinx-blue
  :target: https://paquiteau.github.io/patch-denoising
.. |RELEASE| image:: https://img.shields.io/pypi/v/patch-denoise
   :target: https://pypi.org/project/patch-denoise/
.. |STYLE| image:: https://img.shields.io/badge/style-black-black
   :target: https://github.com/psf/black
.. |LINTER| image:: https://img.shields.io/badge/linter-ruff-inactive
   :target: https://github.com/charliemarsh/ruff
.. |PYVERSION| image:: https://img.shields.io/pypi/pyversions/patch-denoise
   :target: https://pypi.org/project/patch-denoise/
.. |CITATION| image:: https://img.shields.io/badge/paper-hal--openaccess-green
   :target: https://hal.science/hal-03895194
   
This repository implements patch-denoising methods, with a particular focus on local-low rank methods.

The target application is functional MRI thermal noise removal, but this methods can be applied to a wide range of image modalities.

It includes several local-low-rank based denoising methods (see the `documentation <https://paquiteau.github.io/patch-denoising>`_ for more details):

1. MP-PCA
2. Hybrid-PCA
3. NORDIC
4. Optimal Thresholding
5. Raw Singular Value Thresholding

A mathematical description of theses methods is available in the documentation.



Installation
============

patch-denoise requires Python>=3.8


Quickstart
==========

After installing you can use the ``patch-denoise`` command-line.

.. code::

   $ patch-denoise input_file.nii output_file.nii --mask="auto"

See ``patch-denoise --help`` for detailled options.

Documentation and Examples
==========================

Documentation and examples are available at https://paquiteau.github.io/patch-denoising/


Development version
===================

.. code::

   $ git clone https://github.com/paquiteau/patch-denoising
   $ pip install -e patch-denoising[dev,doc,test,optional]
   
Citation
========

If you use this package for academic work, please cite the associated publication, available on `HAL <https://hal.science/hal-03895194>`_ ::

      @inproceedings{comby2023,
        TITLE = {{Denoising of fMRI volumes using local low rank methods}},
        AUTHOR = {Pierre-Antoine, Comby and Zaineb, Amor and Alexandre, Vignaud and Philippe, Ciuciu},
        URL = {https://hal.science/hal-03895194},
        BOOKTITLE = {{ISBI 2023 - International Symposium on Biomedical Imaging 2023}},
        ADDRESS = {Carthagena de India, Colombia},
        YEAR = {2023},
        MONTH = Apr,
        KEYWORDS = {functional MRI ; patch denoising ; singular value thresholding ; functional MRI patch denoising singular value thresholding},
        PDF = {https://hal.science/hal-03895194/file/isbi2023_denoise.pdf},
        HAL_ID = {hal-03895194},
        HAL_VERSION = {v1},
      }

