XNAT for Preclinical Imaging Centers (XNAT-PIC) is a free and open-source Windows desktop application, which offers several tools to expand the XNAT core functionalities to support the preclinical imaging community and to promote open science practices.
- Overview
- Main Features
- Architecture
- Requirements
- Run the App
- Releases
- Roadmap
- License
- Citation
- News
- Contact
- Funding
- Acknowledgments
Schematic view. (A) XNAT-PIC converts to DICOM multimodal images from several vendors, uploads, and annotates preclinical images to the XNAT server. (B) Datasets can be processed via containerized workflows in XNAT. (C) Custom plugins introduce new data types for optical and photoacoustic imaging, enabling users to upload, organize, and view these images directly in XNAT.
Converts raw imaging data from MRI (Bruker) and Optical Imaging (IVIS) systems into the DICOM format.
Uploads DICOM datasets to an XNAT instance, supporting workflows at the project, subject, and experiment levels. The uploader also enables the management of imaging modalities not natively supported by XNAT, such as optical imaging and photoacoustic imaging.
Provides an interface to efficiently cope with different experimental protocols by labelling subjects with dedicated Custom Forms to manage several types of cohorts (e.g. treated/untreated, timepoints, doses, etc..)
The app is a Python desktop application built with Flet and organized in modules:
converter/for conversion workflowsuploader/for XNAT upload workflowscustom_form/for metadata annotationxnat_client/for XNAT API integration
Entry point: main.py.
Python dependencies are listed in requirements.txt:
fletnumpypydicompillowxnatpython-dateutil
From the repository root:
python main.pyThis launches the desktop UI via Flet.
You can download stable and pre-release builds from the GitHub Releases page:
- Latest release notes: v2.1-beta.0
- Direct MSI download (Windows): XNAT-PIC-2.1-beta.0.msi
- All releases: GitHub Releases
See open issues for planned features and known issues.
XNAT-PIC is distributed under the terms of the GNU General Public License (GPL) v3 or later.
See LICENSE.md for details.
If you use XNAT-PIC in your work, please cite:
- S. Zullino, A. Paglialonga, W. Dastrù, D. L. Longo, S. Aime. XNAT-PIC: Extending XNAT to Preclinical Imaging Centers, 2021. DOI/Preprint: https://arxiv.org/abs/2103.02044
-
"Demonstrator 5: XNAT-PIC: expanding XNAT for image archiving and processing to Preclinical Imaging Centers". EOSC-Life website, https://www.eosc-life.eu/d5/
-
"Towards sharing and reusing of preclinical image data". Euro-Bioimaging website, https://www.eurobioimaging.eu/news/towards-sharing-and-reusing-of-preclinical-image-data/
-
"Data Management: Biological and Preclinical Imaging Perspective". Euro-Bioimaging Virtual Pub, February 12th, 2021.
-
"XNAT-PIC: expanding XNAT for image archiving and processing to Preclinical Imaging Centers". Demonstrator 5 from Populating EOSC-Life: Success stories for the Demonstrators – Session 1 from January 13, 2021.
Francesco Gammaraccio
Molecular Imaging Center
Department of Molecular Biotechnology and Health Sciences
Via Nizza 52 | 10126 Torino, Italy
francesco.gammaraccio@unito.it | T +39 011 670 6473
Kranthi Thej Kandula
Molecular Imaging Center
Department of Molecular Biotechnology and Health Sciences
Via Nizza 52 | 10126 Torino, Italy
kranthithej.kandula@unito.it | T +39 011 670 6473
European Union’s Horizon 2020 / Horizon Europe programmes under grant agreements:
- #824087 (EOSC-Life)
- #965345 (HealthyCloud)
- #101058427 (EOSC4Cancer)
- #1011100633 (EUCAIM)
- Alessandro Paglialonga: https://github.com/pagli17
- Stefan Klein, Hakim Achterberg and Marcel Koek — Biomedical Imaging Group Rotterdam, Erasmus Medical Center, Rotterdam
- Matteo Caffini, "Project-Beat--Python": https://github.com/mcaffini/Project-Beat---Python
- Sara Zullino: https://github.com/szullino