Skip to content

Latest commit

 

History

History
95 lines (76 loc) · 4.17 KB

README.rst

File metadata and controls

95 lines (76 loc) · 4.17 KB
Raw

petqc: image quality metrics for quality assessment of PET

DOI Zenodo Package Pythons DevStatus License Documentation CircleCI Codacy

PETQC extracts no-reference IQMs (image quality metrics) from structural (T1w and T2w) and PET (Positron Emission Tomography) data.

PETQC is an open-source project, developed under the following software engineering principles:

  1. Modularity and integrability: PETQC implements a nipype workflow to integrate modular sub-workflows that rely upon third party software toolboxes such as FSL, ANTs and AFNI.
  2. Minimal preprocessing: the PETQC workflows should be as minimal as possible to estimate the IQMs on the original data or their minimally processed derivatives.
  3. Interoperability and standards: PETQC follows the the brain imaging data structure (BIDS), and it adopts the BIDS-App standard.
  4. Reliability and robustness: the software undergoes frequent vetting sprints by testing its robustness against data variability using images from OpenNeuro. Its reliability is permanently checked and maintained with CircleCI.

Citation

Support and communication

The documentation of this project is found here: http://petqc.readthedocs.io/.

Users can get help using the petqc-users google group.

All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/nipreps/petqc/issues.

License information

PETQC adheres to the general licensing guidelines of the NiPreps framework.

PETQC originally derives from, and hence is heavily influenced by, the PCP Quality Assessment Protocol. Please check the NOTICE file for further information.

License

Copyright (c) 2021, the NiPreps Developers.

As of the 21.0.x pre-release and release series, PETQC is licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Acknowledgements

This work is steered and maintained by the NiPreps Community.