Integrative Biomedical Imaging Informatics

Our Vision

Transforming imaging data into knowledge to improve health.

Our Mission

Pioneering, translating and disseminating methods in the information sciences that integrate imaging, clinical and molecular data to understand biology and to improve clinical care.

Recently Awarded Grants

Computing, Optimizing, and Evaluating Quantitative Cancer Imaging Biomarkers
PI(s): Napel, Rubin
(NIH/NCI: 1U01CA187947-01A1)

Qualification and Deployment of Imaging Biomarkers of Cancer Treatment Response
PI: Rubin
(NIH/NCI: 1U01CA190214-01, 06/2015)

Informatics Tools for Optimized Imaging Biomarkers for Cancer Research & Discovery
Subcontract PI: Napel (MGH prime)
(NIH/NCI: U24 CA180927, 09/2014)

Data and Terminology Standards in Imaging Development and Evaluation
PI: Rubin
(FDA 1R24FD004757, 08/2013)

Tools for Linking and Mining Image and Genomic Data in Non-Small Cell Lung Cancer 
co-PIs: Sandy Napel, Sylvia Plevritis 
(NIH: 1R01CA16025101, 09/2011)

Clinically Relevant Regulatory Networks in the Lung Tumor Microenvironment 
PI: Sylvia Plevritis 
(NIH: 1U01CA154960-01, 09/2011)

News and Events


  • New SIIM Fellow: Honors were awarded to Daniel L. Rubin, MD, MS with his induction into the SIIM College of Fellows on Friday, June 1. He is Professor of Biomedical Data Science, Radiology, Medicine (Biomedical Informatics), and Ophthalmology (courtesy) at Stanford University. He is Principal Investigator of two centers in the National Cancer Institute's Quantitative Imaging Network (QIN) and is Director of Biomedical Informatics for the Stanford Cancer Institute. He also leads the Research Informatics Center (RIC) of the School of Medicine. Dr. Rubin's exceptional accomplishments and talents reflect the highest standards of SIIM. - June 5, 2018
  • Sandy Napel and Daniel Rubin awarded an NIH U01 grant "Computing, Optimizing, and Evaluating Quantitative Cancer Imaging Biomarkers" - August 25, 2015
  • Martin Epstein Award at AMIA 2014:  Gimenez F, Wu Y, Burnside ES, Rubin DL. "A Novel Method to Assess Incompleteness of Mammography Report Content." Proceedings of the American Medical Informatics Association; Washington, DC, p. 1758-67