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k-space_wght_msk_for_mri_denoising

k-space weighting and masking for denoising of MRI image without blurring or losing contrast, as well as for brightening of the objects in the image with simultaneous noise reduction (on the example of Agilent FID data). (Python 3)

https://github.com/beatawereszczynska/k-space_wght_msk_for_mri_denoising

Science Score: 67.0%

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    CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 6 DOI reference(s) in README
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    Academic publication links
    Links to: sciencedirect.com, zenodo.org
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    Academic email domains
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    Institutional organization owner
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    Scientific vocabulary similarity
    Low similarity (9.4%) to scientific vocabulary

Keywords

agilent computer-vision computervision denoising denoising-images image image-processing image-reconstruction k-space mri mri-data mri-images mri-reconstruction python python-3 python-script python3
Last synced: 6 months ago · JSON representation ·

Repository

k-space weighting and masking for denoising of MRI image without blurring or losing contrast, as well as for brightening of the objects in the image with simultaneous noise reduction (on the example of Agilent FID data). (Python 3)

Basic Info
  • Host: GitHub
  • Owner: BeataWereszczynska
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 27.4 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
agilent computer-vision computervision denoising denoising-images image image-processing image-reconstruction k-space mri mri-data mri-images mri-reconstruction python python-3 python-script python3
Created about 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License Citation

README.md

k-spacewghtmskforMRI_denoising

DOI

k-space weighting and masking for denoising of MRI image without blurring or losing contrast, as well as for brightening of the objects in the image with simultaneous noise reduction (on the example of Agilent FID data).

Figure1 Figure2

The repository contains:

  1. Python script wghtmskkspace.py.
  2. Description.pdf presenting:
  3. short introduction to the topic,
  4. how the code works,
  5. sample results.
  6. Sample FID data in the mems2019040602.fid folder.
  7. Sample results illustration in Figure1.png and Figure2.png.

Literature reference (for the sample data)

Beata Wereszczyńska, Alcohol-fixed specimens for high-contrast post-mortem MRI, Forensic Imaging, Volume 25, 2021, 200449, ISSN 2666-2256, https://doi.org/10.1016/j.fri.2021.200449. (https://www.sciencedirect.com/science/article/pii/S2666225621000208)

License

The software is licensed under the MIT license. The non-software content of this project is licensed under the Creative Commons Attribution 4.0 International license. See the LICENSE file for license rights and limitations.

You may also like

k-spacemaskingforMRIdenoising - Graduate k-space masking for MRI image denoising and blurring (on the example of Agilent FID data), https://doi.org/10.5281/zenodo.7359195 (https://github.com/BeataWereszczynska/k-spacemaskingforMRIdenoising).

MRIk-space-deriveddetails_edges - k-space based details/edges detection in MRI images with optional k-space based denoising and detail control (data import suitable for Agilent FID files, three binarization methods to choose from), https://doi.org/10.5281/zenodo.7388435 (https://github.com/BeataWereszczynska/MRIk-space-deriveddetails_edges).

Owner

  • Name: Beata Wereszczyńska
  • Login: BeataWereszczynska
  • Kind: user
  • Location: Poland

I'm a Python enthusiast, but also an NMR and MRI physicist (PhD) with broad experience in experimental research.

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: "Wereszczyńska"
    given-names: "Beata"
    orcid: "https://orcid.org/0000-0003-3013-212X"
title: "k-space weighting and masking for denoising of MRI image without blurring or losing contrast, as well as for brightening of the objects in the image with simultaneous noise reduction"
version: v1.0
doi: 10.5281/zenodo.7367057
date-released: 2022-11-26
url: "https://github.com/BeataWereszczynska/k-space_wght_msk_for_MRI_denoising"

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