Collection of all datasets used to develop AIDAqc

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README.md

Collection of Resources for AIDAqc Pipeline

This repository contains various resources related to the AIDAqc pipeline used in the following Publication: Automated quality control of small animal MR neuroimaging data, DOI: tbd. Each subsection for code, input, output, and docs provides more detailed information for each folder or file.

Repository Structure:

  • code/: Here, you can find all the code used for this publication. Detailed information is available in the README of the code folder.

  • input/: This folder contains all datasets and other necessary data. More detailed information regarding each dataset can be found in the respective subfolders.

  • output/: Within this directory, you'll locate the final results generated by the AIDAqc pipeline for each dataset. Detailed information for each dataset's output can be found in their respective subfolders.

  • docs/: For additional documentation related to this project, including extra resources, you can access it via this link or through the README file within this folder.

Additional Information:

This structured dataset was created with reference to the following publication:

DOI:10.1038/s41597-023-02242-8

If you have any questions or need further assistance, please feel free to contact us.

datacite.yml
Title Automated quality control of small animal MR neuroimaging data
Authors Aswendt,Markus;University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany ;ORCID:0000-0003-1423-0934
Kalantari,Aref;University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany ;ORCID:0000-0003-3050-0930
Description This dataset is a super-dataset containing all datasets used to develop the AIDAqc pipeline and corresponds to the following Publication (DOI): tbd
License CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)
References Aref Kalantari, Mehrab Shahbazi, Marc Schneider, Victor Vera Frazão, Avnish Bhattrai, Lorenzo Carnevale, Yujian Diao, Bart A. A. Franx, Francesco Gammaraccio, Lisa-Marie Goncalves, Susan Lee, Esther M. van Leeuwen, Annika Michalek, Susanne Mueller, Alejandro Rivera Olvera, Daniel Padro, Adam C. Raikes, Mohamed Kotb Selim, Annette van der Toorn, Federico Varriano, Roël Vrooman, Patricia Wenk, H Elliott Albers, Philipp Boehm-Sturm, Eike Budinger, Santiago Canals, Silvia De Santis, Roberta Diaz Brinton, Rick M. Dijkhuizen, Elisenda Eixarch, Gianluigi Forloni, Joanes Grandjean, Khan Hekmatyar, Russell E. Jacobs, Ileana Jelescu, Nyoman D. Kurniawan, Giuseppe Lembo, Dario Livio Longo, Naomi S. Sta Maria, Edoardo Micotti, Emma Muñoz-Moreno, Pedro Ramos-Cabrer, Wilfried Reichardt, Guadalupe Soria, Giovanna D. Ielacqua, Markus Aswendt [doi:tba] (IsSupplementTo)
Funding DFG; 431549029 – SFB 1451
Friebe Foundation; T0498/28960/16
Keywords Quality-control
MRI
Preclinical-imaging
DataLad
Resource Type Dataset