QuantImage: An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT
Y.D. Cid, J. Castelli, R. Schaer, N. Scher, A. Pomoni, J.O. Prior, A. Depeursinge
Biomedical Texture Analysis, A. Depeursinge, O.S. Al-Kadi, J.R. Mitchell, Eds., Academic Press, London, United Kingdom, ch. 12, pp. 349–377, 2017.
The processes of radiomics consist of image-based personalized tumor phenotyping for precision medicine. They complement slow, costly, and invasive molecular analysis of tumoral tissue. Whereas the relevance of a large variety of quantitative imaging biomarkers has been demonstrated for various cancer types, most studies were based on 2D image analysis of relatively small patient cohorts. In this work, we propose an online tool for automatically extracting 3D state-of-the-art quantitative imaging features from large batches of patients. The developed platform is called QuantImage and can be accessed from any web browser. Its use is straightforward and can be further parameterized for refined analyses. It relies on a robust 3D processing pipeline allowing normalization across patients and imaging protocols. The user can simply drag-and-drop a large zip file containing all image data for a batch of patients and the platform returns a spreadsheet with the set of quantitative features extracted for each patient. It is expected to enable high-throughput reproducible research and the validation of radiomics imaging parameters to shape the future of noninvasive personalized medicine.
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AUTHOR="Cid, Y.D. and Castelli, J. and Schaer, R. and Scher, N. and
Pomoni, A. and Prior, J.O. and Depeursinge, A.",
TITLE="{Q}uant{I}mage: {A}n Online Tool for High-Throughput {3D}
Radiomics Feature Extraction in {PET-CT}",
BOOKTITLE="Biomedical Texture Analysis",
PUBLISHER="Academic Press",
YEAR="2017",
editor="Depeursinge, A. and Al-Kadi, O.S. and Mitchell, J.R.",
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type="",
chapter="12",
pages="349--377",
address="London, United Kingdom",
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