Skip to main content

Susceptibility Distortion Correction (SDC) workflows for EPI MR schemes.

Project description

Latest Version https://codecov.io/gh/nipreps/sdcflows/branch/master/graph/badge.svg?token=V2CS5adHYk https://circleci.com/gh/nipreps/sdcflows.svg?style=svg https://github.com/nipreps/sdcflows/workflows/Deps%20&%20CI/badge.svg

SDCFlows (Susceptibility Distortion Correction workFlows) is a Python library of NiPype-based workflows to preprocess B0 mapping data, estimate the corresponding fieldmap and finally correct for susceptibility distortions. Susceptibility-derived distortions are typically displayed by images acquired with EPI (echo-planar imaging) MR schemes.

The library is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input.

This open-source neuroimaging data processing tool is being developed as a part of the MRI image analysis and reproducibility platform offered by NiPreps.

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

sdcflows-2.7.0.tar.gz (10.5 MB view details)

Uploaded Source

Built Distribution

sdcflows-2.7.0-py3-none-any.whl (10.0 MB view details)

Uploaded Python 3

File details

Details for the file sdcflows-2.7.0.tar.gz.

File metadata

  • Download URL: sdcflows-2.7.0.tar.gz
  • Upload date:
  • Size: 10.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for sdcflows-2.7.0.tar.gz
Algorithm Hash digest
SHA256 82b1d4eecf1d2e515c9def24522e520c889d08976390d4b8f58891fffb30d6d4
MD5 58dbc2339b1b5605c8bf137347123fbd
BLAKE2b-256 ab91109b9641f5a8ecd72a8de836a06fb5283bb41f4ca941e2b368d5cd4952d8

See more details on using hashes here.

Provenance

File details

Details for the file sdcflows-2.7.0-py3-none-any.whl.

File metadata

  • Download URL: sdcflows-2.7.0-py3-none-any.whl
  • Upload date:
  • Size: 10.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for sdcflows-2.7.0-py3-none-any.whl
Algorithm Hash digest
SHA256 3621fe4fbc4274ee20543829d96456af8564bd0df0f1dd1f209b1b1dfbe1f7ae
MD5 84f5214259c1231a0f91c121a96c4d33
BLAKE2b-256 1d5bb2120111e627240be910bb91afe6819db88c028c69541008012ab0d1ab86

See more details on using hashes here.

Provenance

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