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Article

Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network

by
Keyvan Farahani
1,*,
Jayashree Kalpathy-Cramer
2,
Thomas L. Chenevert
3,
Daniel L. Rubin
4,
John J. Sunderland
5,
Robert J. Nordstrom
1,
John Buatti
6 and
Nola Hylton
7
1
Cancer Imaging Program, National Cancer Institute, Bethesda, MD, USA
2
Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
3
Department of Radiology, University of Michigan, Ann Arbor, MI, USA
4
Department of Radiology, Biomedical Data Science, and Medicine (Biomedical Informatics Research), Stanford University, Palo Alto, CA, USA
5
Department of Radiology, University of Iowa, Iowa City, IA, USA
6
Department of Radiation Oncology, University of Iowa, Iowa City, IA, USA
7
Department of Radiology, University of California San Francisco, San Francisco, CA, USA
*
Author to whom correspondence should be addressed.
Tomography 2016, 2(4), 242-249; https://doi.org/10.18383/j.tom.2016.00265
Submission received: 5 September 2016 / Revised: 3 October 2016 / Accepted: 2 November 2016 / Published: 1 December 2016

Abstract

The Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI) conducts research in development and validation of imaging tools and methods for predicting and evaluating clinical response to cancer therapy. Members of the network are involved in examining various imaging and image assessment parameters through network-wide cooperative projects. To more effectively use the cooperative power of the network in conducting computational challenges in benchmarking of tools and methods and collaborative projects in analytical assessment of imaging technologies, the QIN Challenge Task Force has developed policies and procedures to enhance the value of these activities by developing guidelines and leveraging NCI resources to help their administration and manage dissemination of results. Challenges and Collaborative Projects (CCPs) are further divided into technical and clinical CCPs. As the first NCI network to engage in CCPs, we anticipate a variety of CCPs to be conducted by QIN teams in the coming years. These will be aimed to benchmark advanced software tools for clinical decision support, explore new imaging biomarkers for therapeutic assessment, and establish consensus on a range of methods and protocols in support of the use of quantitative imaging to predict and assess response to cancer therapy.
Keywords: quantitative imaging; cancer therapy; crowdsourcing; challenge; collaborative project quantitative imaging; cancer therapy; crowdsourcing; challenge; collaborative project

Share and Cite

MDPI and ACS Style

Farahani, K.; Kalpathy-Cramer, J.; Chenevert, T.L.; Rubin, D.L.; Sunderland, J.J.; Nordstrom, R.J.; Buatti, J.; Hylton, N. Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network. Tomography 2016, 2, 242-249. https://doi.org/10.18383/j.tom.2016.00265

AMA Style

Farahani K, Kalpathy-Cramer J, Chenevert TL, Rubin DL, Sunderland JJ, Nordstrom RJ, Buatti J, Hylton N. Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network. Tomography. 2016; 2(4):242-249. https://doi.org/10.18383/j.tom.2016.00265

Chicago/Turabian Style

Farahani, Keyvan, Jayashree Kalpathy-Cramer, Thomas L. Chenevert, Daniel L. Rubin, John J. Sunderland, Robert J. Nordstrom, John Buatti, and Nola Hylton. 2016. "Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network" Tomography 2, no. 4: 242-249. https://doi.org/10.18383/j.tom.2016.00265

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