Skip to main content

mrid

mrid is a library for preprocessing of 3D images, particularly medical images.

It provide interfaces for many medical image processing tools such as SimpleElastix, HD-BET, SynthStrip, CTSeg. Note that those libraries are not bundled, installation instructions are included in all examples below.

Installation

Either run

pip install mrid-python

or

pip install git+https://github.com/inikishev/mrid

Registering images with SimpleITK-SimpleElastix

SimpleElastix is a robust tool for image registration which works really well out-of-the-box. It works on both Windows and Linux.

See this notebook for how to install and use it. image

Skullstripping MRI scans with HD-BET

HD-BET is a model that performs skullstripping of pre- and post-constrast T1, T2 and FALIR MRIs. It works on both Windows and Linux.

See this notebook for how to install and use it image

Skullstripping with SynthStrip

SynthStrip is a skull-stripping tool that works with many different image types and modalities, including MRI, DWI, CT, PET, etc.

See this notebook for how to install and use it image

Skullstripping and segmentation of CT images with CTseg

CTseg can skull-strip CT images and perform their segmentation, it also registers them to a common space (see its README). Note that it can be very slow for 512x512 series (can take few hours), but you can downsample to 256x256. If you only need to quickly skullstrip CT scans without warping them you can use SynthStrip.

TODO!!!

Example workflow - preprocessing MRIs to BraTS format

Many BraTS datasets are provided as skullstripped images in SRI24 space. See this notebook for how to process raw scans to this format.

image

(T1n image looks weird because that's just how it is in the zenodo dataset)

References

The MRIs for all images above are from https://zenodo.org/records/7213153.

Colin Vanden Bulcke. (2022). Open-Access DICOM MRI session (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7213153

Release files for mrid-python 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mrid-python 0.1.5
File Size Uploaded
mrid_python-0.1.5.tar.gz 36.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for mrid-python 0.1.5
File Interpreter ABI Platform
mrid_python-0.1.5-py3-none-any.whl Python 3 none any Details

Total release size: 80.3 kB

Release files / mrid_python-0.1.5.tar.gz

Download URL mrid_python-0.1.5.tar.gz
Size 36.3 kB
Tags Source
SHA-256 checksum
How to use checksums
433bebafb8ca508eb8ed3bce87ebeb2cf37d09b73307ac0c9d4116cd9b745ca1
BLAKE2b-256 checksum
How to use checksums
cb2cf3ba3f5f9c1d7d64d0b3d5436b1abd01944e44544f86f38dca4789a6837c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 21, 2025.

Transparency log

Release files / mrid_python-0.1.5-py3-none-any.whl

Download URL mrid_python-0.1.5-py3-none-any.whl
Size 44.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0757f34c8b54424243a96da53fc36e0d324c8fc9d15972aee97e499eb2574264
BLAKE2b-256 checksum
How to use checksums
4ef2801f6d796229ef80c290020a14448fe6d437e7c206d18ae2b3290d706d5c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Dec 21, 2025.

Transparency log

Release history Release notifications | RSS feed

This release

0.1.5 This release

2 release files

0.1.4

2 release files

0.1.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page