Skip to main content

Quality assurance tools for MRI geometric distortion

Project description

mri_distortion_toolkit

codecov tests docsPyPI version

This code enables characterization, reporting, and correction of geometric distortion in Magnetic Resonance Imaging.

For the measurement of such distortions, see here.

The workflow steps are below, but all steps have well defined input/output so you can use any part of this code independently from the other parts. For a tutorial on each step, click on the diagram below. For an example of our automated reporting template see here

flowchart LR
    A[Marker <br>Extraction]--->B[Marker <br>Matching]
    B[Marker <br>Matching]--->C[Field <br> Calculation] & E[Automated <br>reporting]
    C[Field <br> Calculation]-->D[Spherical Harmonic <br>Analysis]
    D[Spherical Harmonic <br>Analysis]-->E[Automated <br>reporting];
    D[Spherical Harmonic <br>Analysis]-->F[Distortion Correction]

    click A "https://acrf-image-x-institute.github.io/mri_distortion_toolkit/code_docs.html#MRI_DistortionQA.MarkerAnalysis.MarkerVolume"
    click B "https://acrf-image-x-institute.github.io/mri_distortion_toolkit/code_docs.html#MRI_DistortionQA.MarkerAnalysis.MatchedMarkerVolumes"
    click C "https://acrf-image-x-institute.github.io/mri_distortion_toolkit/code_docs.html#MRI_DistortionQA.FieldCalculation.ConvertMatchedMarkersToBz"
    click D "https://acrf-image-x-institute.github.io/mri_distortion_toolkit/code_docs.html#MRI_DistortionQA.FieldAnalysis.SphericalHarmonicFit"
    click E "https://acrf-image-x-institute.github.io/mri_distortion_toolkit/code_docs.html#MRI_DistortionQA.Reports.MRI_QA_Reporter"

Setup/Build/Install

pip install mri_distortion_toolkit

Usage

Detailed documentation is here.

Directory Structure

  • docsrc markdown/rst source documentation
  • tests test cases
  • MRI_DistortionQA source code
  • examples source code for the worked examples

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mri_distortion_toolkit-0.11.0.tar.gz (51.7 kB view details)

Uploaded Source

Built Distribution

mri_distortion_toolkit-0.11.0-py3-none-any.whl (55.3 kB view details)

Uploaded Python 3

File details

Details for the file mri_distortion_toolkit-0.11.0.tar.gz.

File metadata

File hashes

Hashes for mri_distortion_toolkit-0.11.0.tar.gz
Algorithm Hash digest
SHA256 f5021e793a7d3417120beb39d2561e67c1ce5188b8c217251958a299f15ddd60
MD5 afb822f8e94061fa7288ff93a1d19f8f
BLAKE2b-256 03c15e402d2ba30766be22011c006fb92065517283ead920eff61dd15aa15a7a

See more details on using hashes here.

File details

Details for the file mri_distortion_toolkit-0.11.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mri_distortion_toolkit-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6de285808a6291180294780f752ec7ec1b8d31c5d0cde6f3e50f03e085715558
MD5 63a7d6a2a5592f5a6af60f69f824ab3b
BLAKE2b-256 8477f27257ee998a94b6edeee021262b4409625a104d8ef45eac527e3f80cabb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page