Data

Tools

Indexes

Applications

Experiments

Open Source Science

mri_k-space-derived_details_edges

k-space based details/edges detection in MRI images with optional k-space based denoising and detail control (on the example of Agilent FID data). (Python 3)

https://github.com/beatawereszczynska/mri_k-space-derived_details_edges

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 8 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: sciencedirect.com, zenodo.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (11.9%) to scientific vocabulary

Keywords

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

Repository

k-space based details/edges detection in MRI images with optional k-space based denoising and detail control (on the example of Agilent FID data). (Python 3)

Basic Info
  • Host: GitHub
  • Owner: BeataWereszczynska
  • License: other
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 31.5 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
agilent computer-vision computervision edge-detection image image-analysis image-details-detection image-edge-detection image-processing k-space mri mri-data mri-images python python-3 python-script python3
Created over 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License Citation

README.md

MRIk-space-deriveddetails_edges

DOI

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).

FigureA

Figure A. Sample results for details/edges detection with detail control and simple thresholding.

FigureB

Figure B. Sample results for details/edges detection with denoising, detail control and adaptive thresholding.

The repository contains:

  1. Python script kspacedetedg.py.
  2. Description.pdf presenting:
  3. short introduction to the topic,
  4. how the code works step by step,
  5. sample results with commentary.
  6. Sample FID data in the sems2019020303.fid folder.
  7. Sample results illustrations in FigureA.png and FigureB.png.

References

1. Collection of 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)

2. Denoising:

Beata Wereszczyńska, 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, 2022, https://doi.org/10.5281/zenodo.7367057. (https://github.com/BeataWereszczynska/k-spacewghtmskforMRI_denoising)

3. Detail control:

Beata Wereszczyńska, Graduate k-space masking for MRI image denoising and blurring, 2022, https://doi.org/10.5281/zenodo.7359195. (https://github.com/BeataWereszczynska/k-spacemaskingforMRIdenoising)

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

SwellingtabletfrontsDkfromMRIT2or_img - Tool for characterizing the swelling of tablets immersed in a solution. Creates time plots and calculates eroding front's diffusion rate D and the rate of the swelling k from time series of either T2-maps or (properly contrasted, e.g. T2-weighted) MRI images in FDF (file format native for Agilent MRI scanners) or Text Image format. This software is suitable for swelling matrix tablets forming a membrane-like structure in contact with the solution in which they are immersed, https://doi.org/10.5281/zenodo.7262466 (https://github.com/BeataWereszczynska/SwellingtabletfrontsDkfromMRIT2or_img).

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 based details/edges detection in MRI images with optional k-space based denoising and detail control"
version: v1.0
doi: 10.5281/zenodo.7388435
date-released: 2022-12-01
url: "https://github.com/BeataWereszczynska/MRI_k-space-derived_details_edges"

GitHub Events

Total
Last Year

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 65
  • Total Committers: 1
  • Avg Commits per committer: 65.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 65
  • Committers: 1
  • Avg Commits per committer: 65.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Beata Wereszczyńska b****a@g****m 65

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels