The NCI Imaging Data Commons: Towards FAIR imaging data via
standardization and openness for AI

by Andrey Fedorov
5 September 2022 , 7-8 pm CEST  

REGISTRATION LINK:

https://us02web.zoom.us/webinar/register/WN_6p1_0UZQTnmkIpjEFQVEMQ

Abstract: The National Cancer Institute (NCI) Cancer Research Data
Commons (CRDC) aims to establish a national cloud-based data science
infrastructure. Imaging Data Commons (IDC) is a new component of CRDC
supported by the Cancer Moonshot. The goal of IDC is to enable a broad
spectrum of cancer researchers, with and without imaging expertise, to
easily access and explore the value of deidentified imaging data and
to support integrated analyses with nonimaging data. We achieve this
goal by colocating versatile imaging collections with cloud-based
computing resources and data exploration, visualization, and analysis
tools. The IDC went into production in September 2021, and includes a
growing number of radiology and digital pathology collections
accompanied by annotations and analysis results. IDC provides access
to curated imaging collections, and a growing number of analysis use
cases that aim to demonstrate the value of a data commons framework
applied to cancer imaging research. In this presentation I will
discuss the current status of NCI Imaging Data Commons and highlight
the opportunities it presents towards improved reproducibility and
openness for AI imaging research.

Bio: Andrey Fedorov is an Associate Professor in Radiology at the
Surgical Planning Laboratory (SPL), Department of Radiology, Brigham
and Women’s Hospital and Harvard Medical School. 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, most notably 3D Slicer
(http://slicer.org). Together with Dr. Kikinis he is currently a co-PI
of the team tasked with building the NCI Imaging Data Commons
(https://imaging.datacommons.cancer.gov).