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-2.2.2.tar.gz (9.9 MB view details)

Uploaded Source

Built Distribution

sdcflows-2.2.2-py3-none-any.whl (10.0 MB view details)

Uploaded Python 3

File details

Details for the file sdcflows-2.2.2.tar.gz.

File metadata

  • Download URL: sdcflows-2.2.2.tar.gz
  • Upload date:
  • Size: 9.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.5

File hashes

Hashes for sdcflows-2.2.2.tar.gz
Algorithm Hash digest
SHA256 f6d1facbb7a123d40f5f074bfece430e21973c1b23092b44f8dccb9de1541e0a
MD5 1e00520561678bb9e401c0e859f95cb0
BLAKE2b-256 3d5a4645af36588959a011498a61425318353423ef2f239c12d3829297f9f1ca

See more details on using hashes here.

Provenance

File details

Details for the file sdcflows-2.2.2-py3-none-any.whl.

File metadata

  • Download URL: sdcflows-2.2.2-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/3.8.5

File hashes

Hashes for sdcflows-2.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 1a341b1c00cc71b72a8bbafa2703b23a64402e4c8c7513c0e6484354cedef1cd
MD5 2c86c58acb1a52039ba60c0e3113bebc
BLAKE2b-256 5f0d5fc52784624f5d3edb56674aaf516b98bd54fdb0668450d600f7e6d834d5

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