Data Curation made easy
Automated Data Curation and Validation
Check the BIDS Specification Download PET2BIDS
Once data are curated into BIDS, it becomes easier to preprocess and analyze them using standardized tools and pipelines. Check PETPrep for automated preprocessing. PETPrep is a robust and open-source preprocessing pipeline for positron emission tomography (PET) imaging developed within the NiPreps framework. It provides a robust, automated, and BIDS-compliant solution for transforming raw PET data into analysis-ready outputs with minimal user input. PETPrep performs essential preprocessing steps such as motion correction, segmentation, co-registration between PET and MRI, partial volume correction, normalization, and extraction of regional time–activity curves. By integrating best-in-class tools from widely used neuroimaging software packages, PETPrep ensures high-quality, reproducible preprocessing while offering comprehensive visual reports and detailed error tracking to support transparency and quality control in PET studies.
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Bloodstream and PETFit are two new open-source BIDS apps that provide access to the capabilities of the kinfitr R package for PET modelling as automated pipelines for BIDS data. Both tools are designed for reproducible processing while remaining highly customisable through browser-based configuration interfaces. Bloodstream processes raw PET BIDS arterial blood data, producing quantification-ready input functions through modelling and interpolation of parent fraction, plasma-to-blood ratio, and metabolite-corrected arterial input function curves. PETFit ingests derivative PET time activity curve data (e.g. from PETPrep) and input function data (e.g. from Bloodstream) to perform pharmacokinetic modelling, supporting both invasive models and reference tissue approaches along with detailed analysis reports
The BIDS extension for Positron Emission Tomography (PET-BIDS) (Norgaard et al., 2022) provides nomenclature for structured data and metadata, including all the necessary information to share and report on PET blood and metabolite (Knudsen et al., 2020). Here we present PET2BIDS, developed in both Matlab and Python, allowing the conversion of DICOM (DICOM PS3.3 2020b - Information Object Definitions, 2020) and ECAT (CTI/Siemens proprietary data format) PET imaging data and metadata (e.g., timing information such as ‘time zero’ or blood measurements) into files that follow the BIDS specification (nifti, json, tsv).