IBIIS-AIMI Seminar: Andrey Fedorov, PhD

Abstract: The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The National Cancer Institute (NCI) Imaging Data Commons (IDC) hosts over 50 TB of diverse publicly available cancer image data spanning radiology and microscopy domains. By harmonizing all data based on industry standards and colocalizing it with analysis and exploration resources, IDC aims to facilitate the development, validation, and clinical translation of AI tools and address the well-documented challenges of establishing reproducible and transparent AI processing pipelines. Balanced use of established commercial products with open-source solutions, interconnected by standard interfaces, provides value and performance, while preserving sufficient agility to address the evolving needs of the research community. Emphasis on the development of tools, use cases to demonstrate the utility of uniform data representation, and cloud-based analysis aim to ease adoption and help define best practices. Integration with other data in the broader NCI Cancer Research Data Commons infrastructure open opportunities for multiomics studies incorporating imaging data to further empower the research community to accelerate breakthroughs in cancer detection, diagnosis, and treatment. The presentation will discuss the recent developments in IDC, highlighting resources, demonstrations and examples that we hope can help you improve your everyday imaging research practices - both those that use public and internal datasets. 

Bio: Andrey Fedorov, PhD (https://connects.catalyst.harvard.edu/Profiles/display/Person/71748) is a researcher at Brigham and Women's Hospital (BWH) and Associate Professor in Radiology at Harvard Medical School. Andrey is the technical PI of the team tasked with building National Cancer Institute Imaging Data Commons (IDC). A computer scientist by training, Andrey spent the past 15 years at the BWH Surgical Planning Lab working on translation and evaluation of image computing tools in clinical research applications. He is dedicated to developing infrastructure and best practices to help imaging researchers improve transparency of their studies, simplify data sharing and make their analyses more easily accessible and reproducible by others.

Attendance is open to the Stanford community. If you would like to attend in-person or on Zoom, please contact the AIMI Center at aimicenter@stanford.edu.