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3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

1Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
2University of Iowa, Iowa City, IA, USA.
3Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
4Kitware Inc, Clifton Park, NY, USA.
5GE Research, Niskayuna, NY, USA.
6Isomics, Inc., Cambridge, NY, USA.
Publication Date:
Magnetic Resonance Imaging
Volume Number:
Issue Number:
Magn Reson Imaging. 2012 Nov;30(9):1323-41.
PubMed ID:
cancer imaging, quantitative imaging, software tools, medical imaging, Imaging biomarker, image analysis, MRI, PET, CT, Brain, Head and neck, glioblastoma, cancer treatment response
Appears in Collections:
U01 CA151261/CA/NCI NIH HHS/United States
P41 EB015898/LM/NLM NIH HHS/United States
P41 RR013218/RR/NCRR NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
R01 CA111288/CA/NCI NIH HHS/United States
U01 CA140206/CA/NCI NIH HHS/United States
U01 CA154601/CA/NCI NIH HHS/United States
R00 LM009889/LM/NLM NIH HHS/United States
Generated Citation:
Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. PMCID: PMC3466397.
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Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer.

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