Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network
Year: 2016
Type: article
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.
Source: Tomography
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: Informatics Tools for Optimized Imaging Biomarkers for Cancer Research&Discovery, G216154224, G2550767902, Quantitative Imaging for Assessing Breast Cancer Response to Treatment, Computerized Quantitative Imaging Assessment of Tumor Burden, Quantitative MRI of Glioblastoma Response, G6784455532, Qualification and Deployment of Imaging Biomarkers of Cancer Treatment Response, G8135549017, G9000006023, G9000094240, G9000157192
OpenAlex ID: W2587681779
