Andriy Fedorov, PhD
Associate Professor of Radiology
Department of Radiology
Brigham and Women’s Hospital
Harvard Medical School
National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) (https://datacommons.cancer.gov/) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) (https://imaging.datacommons.cancer.gov/) is a new component of CRDC supported by the Cancer Moonshot™, which aims to enable a broad spectrum of cancer researchers to easily access and explore the value of de-identified imaging data, and to support integrated analyses with non-imaging data. We achieve this goal by co-locating versatile imaging collections with cloud-based compute resources, and visualization and analysis tools. The IDC pilot was released in October 2020, and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. IDC will empower cancer researchers with and without imaging expertise to fully explore the value of imaging data.
Andrey joined SPL in 2009 after obtaining his PhD in Computer Science from The College of William and Mary in Virginia. His research is in translation and validation of medical image computing technology in clinical research applications, with the focus on quantitative imaging, imaging informatics and image-guided interventional procedures. Andrey is committed to advancing the role of reproducible science, data sharing and open source software in academic research. He has contributed to a number of open source projects and public datasets. Together with Ron Kikinis, he is a co-PI of the Imaging Data Commons (IDC) project. IDC is a new component of the NCI Cancer Research Data Commons (CRDC), connecting cancer researchers with publicly available imaging datasets, resources for exploring those datasets and identifying relevant cohorts, and other components of CRDC that will host additional data types and support computation on the defined cohorts.