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

Graduate k-space masking for MRI image denoising and blurring (on the example of Agilent FID data). (Python 3)

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

Science Score: 23.0%

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    Found 6 DOI reference(s) in README
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    Links to: sciencedirect.com, zenodo.org
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    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: 5 months ago · JSON representation

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Graduate k-space masking for MRI image denoising and blurring (on the example of Agilent FID data). (Python 3)

Basic Info
  • Host: GitHub
  • Owner: BeataWereszczynska
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 27.2 MB
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  • Stars: 2
  • Watchers: 1
  • Forks: 0
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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 over 3 years ago · Last pushed almost 3 years ago

https://github.com/BeataWereszczynska/k-space_masking_for_MRI_denoising/blob/main/ 

# k-space_masking_for_MRI_denoising

[![DOI](https://zenodo.org/badge/568669180.svg)](https://zenodo.org/badge/latestdoi/568669180)

Graduate k-space masking for MRI image denoising and blurring (on the example of Agilent FID data).

![Figure1](Fig1.png)
![Figure2](Fig2.png)

## The repository contains:
1. Python script **grad_mask_kspace.py**.
2. **Description.pdf** presenting:
- short introduction to the topic,
- how the code works,
- sample results.
3. Sample FID data in the **mems_20190406_02.fid** folder.
4. Sample results illustration in **Fig1.png** and **Fig2.png**.

## Literature reference (for the sample data)
Beata Wereszczyska, ***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-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), https://doi.org/10.5281/zenodo.7367057 (https://github.com/BeataWereszczynska/k-space_wght_msk_for_MRI_denoising).

**MRI_k-space-derived_details_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/MRI_k-space-derived_details_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.

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