Jeffrey Siewerdsen
Professor
The University of Texas MD Anderson Cancer Center at Houston
Department of Imaging Physics
Imaging and Data Science for Surgical Guidance
Dr. Siewerdsen heads the Surgineering Lab and Surgical Data Science Program at The University of Texas
MD Anderson Cancer Center, with close collaborations in Imaging Physics (the Image-Guided Cancer
Therapy Program) and the Division of Surgery (The IDEAS Lab). Research in the Surgineering Lab focuses
on development and implementation of cutting-edge systems for image-guided surgery, including
technologies for high-precision intervention and data science methods to enable the next evolution in
surgical practice. Technologies include surgical navigation, robotics, and intraoperative imaging (CT,
ultrasound, MRI, and endoscopic video). Surgical data science topics include capture of intraoperative
image and time-series data, development of automated feature extraction methods, and design /
optimization of predictive models for postoperative outcomes. Closely related “Surgineering” activity
includes systems engineering / workflow optimization and surgical process modeling. Projects include
robotically assisted endoscopic brain surgery, deformable image registration for lung interventions,
development of a novel robot for orthopaedic surgery, and deep-learning analytics (automatic
segmentation, registration, and feature extraction) in intraoperative CT, MRI, and ultrasound images.
Resources include an image-guided OR laboratory, surgical navigation systems, high-speed computing, an
ever-expanding surgical instrumentarium, medical imaging phantoms, and 3D printing and machining.
Keywords: medical imaging; data science; image-guided surgery; surgical robotics; surgical navigation.
Education & Training
PhD - University of Michigan - 1998