CIM-XNAT
A XNAT service for archiving and
processing preclinical medical images is available at
EUBI-XNAT.
Small animal imaging facilities are highly specialized centers
that provide the research community access to cutting-edge
imaging technologies. These centers have therefore to deal with
the complexity and the variety of preclinical image datasets in
terms of archiving and retrieving image datasets as well as for
the management and processing. To date, no custom or standard
solutions are available to imaging centers to fullfill these
tasks.
XNAT natively supports multiple imaging modalities,
such as MR, PET, CT, and US. We are extending XNAT datatypes to
other preclinical imaging modalities, such as Optoacoustic (OA)
and Optical Imaging (OI).
We have overcome these limitations through the integration of an open-source archiving platform commonly exploited at clinical level based on XNAT with customizable tools for automated image processing. The developed platform can provide the following workflow:
- importing multiple imaging datasets acquired through several instrumentations and modalities either in DICOM (1) or proprietary formats via DICOM converter (2);
- managing different experimental protocols importing user-defined variables (treated/untreated groups, different timepoints, doses, ...);
- image processing tool accepting raw data (3) or an XNAT image processing pipeline accepting as input DICOM files (4) to produce parametric images by calling user-proprietary image-analysis script.
In the near future, we offer the following services:
- Each user can, after registration, create his/her own projects and upload DICOM data.
- Users can run external applications and shell scripts (pipeline) passing the required parameters to the application to download the data, process it and import the processed data back to XNAT. To date Diffusion Weigthed Imaging (DWI) processing pipelines that cun run at project/subject level are available on our XNAT instance.
- Users can either use previously imported mask on XNAT or create mask directly on XNAT (beta) to obtain parametric images.
XNAT administrators: Sara Zullino
Acknowledgements
XNAT home page: http://www.xnat.org
User documentation: https://wiki.xnat.org/documentation
Group Leaders:
