To facilitate quantitative analysis of FDG PET scans in clinical trials, we have developed open source software (extensions) for 3D Slicer. This website provides an overview of available software, short introductory videos, and links to source code available on github.


PETDICOMExtension PET DICOM Extension
The PET DICOM Extension provides tools to import DICOM PET images into Slicer and performs Standardized Uptake Value (SUV) normalization. Specifically, it calculates Standardized Uptake Value (SUV) conversion factors and creates a corresponding Real World Value Mapping file.

Source code: https://github.com/QIICR/Slicer-PETDICOMExtension
Documentation: https://www.slicer.org/wiki/Documentation/4.6/Extensions/PETDICOM




PET-IndiC PET IndiC
The PET-IndiC Extension allows for fast segmentation of regions of interest and calculation of quantitative indices.
Source code: https://github.com/QIICR/Slicer-QuantitativeIndicesExt
Documentation: https://www.slicer.org/wiki/Documentation/4.6/Extensions/PET-IndiC





PETLiverUptakeMeasurementIcon PET Liver Uptake Measurement
This tool allows automated measurement of liver uptake in SUV normalized FDG-18 whole-body PET scans. A detailed description and evaluation of the method can be found in paper "Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans", which was published in Medical Physics.
Source code: https://github.com/QIICR/PETLiverUptakeMeasurement
Documentation: https://www.slicer.org/wiki/Documentation/4.6/Extensions/PETLiverUptakeMeasurement




PETTumorSegmentationExtensionIcon PET Tumor Segmentation
This tool provides an Editor-Effect for semi-automated segmentation of tumors and hot lymph nodes in PET scans. A detailed description and evaluation of the method can be found in paper "Semiautomated Segmentation of Head and Neck Cancers in 18F-FDG PET Scans: A Just-Enough-Interaction Approach", which was published in Medical Physics.

Source code: https://github.com/QIICR/PETTumorSegmentation
Documentation: https://www.slicer.org/wiki/Documentation/4.6/Extensions/PETTumorSegmentation





Acknowledgements
This work was supported in part by NIH grant U01 CA140206 as well as the Quantitative Image Informatics for Cancer Research (QIICR) project (U24 CA180918).

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The contents of this website does not necessarily represent the official views of the NIH/NCI.