VISE Spring Seminar – Ross Whitaker, PhD 2.8.24
Ross Whitaker, PhD
Professor in the School of Computing and the Scientific Computing and Imaging Institute
University of Utah
Date: Thursday, February 8, 2024
Time: 11:45 a.m. Lunch, 12:00 p.m. start
Location: Stevenson 5326
Title: An Image-Based, Deep-Phenotyping Analysis Toolset, Repository, and Online Clinician Interface for Craniosynostosis
Craniosynostosis, or abnormal cranial suture fusion, affects up to 1 in 2500 children born in the United States and results in abnormal skull morphology and an elevated risk of intracranial hypertension. Significant numbers of patients are treated through either minimally invasive or reconstructive surgeries, for which the timing and methodologies can affect outcomes.
There is currently no objective, quantitative clinical tool for characterizing or quantifying the overall morphologic properties of craniosynostosis, and thus treatment decisions are based on the particular training, background, and subjective judgments of clinicians. Here we present our work on building a data-driven approach for a comprehensive evaluation of pediatric skull morphology, which relies on a statistical shape analysis and an automated pipeline for processing head-CT for pediatric patients. These tools are incorporated into an online portal, CranioRate.org, which allows clinicians to upload CT scans and receive quantitative evaluations of specific patients. These efforts have resulted in findings, for instance, on the effects of treatment and longitudinal outcomes. In this talk we describe the methodologies, the underlying data, and results to date on these efforts.
Ross Whitaker earned a B.S. degree in Electrical Engineering and Computer Science from Princeton University in 1986, and a Ph.D. in Computer Science from the University of North Carolina in 1994. Since 2000 he has been at the University of Utah, where he is a Professor in the School of Computing and the Scientific Computing and Imaging Institute. He is a recipient of the NSF Career Award and an IEEE and AIMBE Fellow. He teaches discrete math, scientific visualization, probability and statistics, and image processing. He leads a research group in image analysis, geometry processing, and scientific computing, with a variety of projects supported by both federal agencies and industrial contracts. His published works have received over 17,000 citations.