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Advanced Surface-Guided Radiation Therapy

Transforming surface guided radiation therapy with low-cost RGB cameras and neural networks for real-time patient tracking and internal anatomy estimation.

Recent Accomplishments

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May 12, 2023

Best in Physics award at AAPM 2023

Awarded to the top 15 abstracts out of 2200+ submissions, placing in the top 1% of all research presented at the conference.

May 06, 2024

Atharva Peshkar and Mohamed Eldib win awards for AAPM 2024

Both researchers recognized for outstanding contributions in medical physics, with awards for innovation and excellence.

October 16, 2023

Computer vision project funded by CU Anschutz Cancer Center

Secured funding for computer vision surface imaging breast DIBH project with very positive reviews from the Cancer Center.

June 22, 2023

First prize in AAPM Rocky Mountain Chapter 'Med Phys Slam'

Won first prize in the competition and represented the Rocky Mountain Chapter at the AAPM annual meeting in Houston.

February 03, 2024

Benchmarking trial begins for Computer Vision technique

Started benchmarking our Computer Vision patient alignment technique against the current gold standard IR-marker motion tracking.

Project Overview

Traditional surface-guided radiation therapy (SGRT) relies on fixed, expensive hardware with limited adaptability. Our approach replaces this with low-cost RGB cameras and neural networks, enabling real-time patient pose tracking and internal anatomy estimation from external surfaces.

Improved Access

Improves access to simulation-free treatment for ~50% of patients currently excluded

Reduced Clinic Visits

Leverages diagnostic CTs and video-based pose tracking to reduce clinic visits

Higher Precision

Models skeletal and soft tissue shifts using deformation models for higher precision

This innovation supports simulation-free workflows — eliminating the need for CT simulation in palliative treatment and reducing delays, burden, and cost.

This work builds on advanced computer vision techniques including SMPL-based modeling and pose estimation, applied in the context of real-world radiation oncology workflows.

Multi-View Demonstration

Simultaneous visualization of RGB, depth, pose tracking, and internal anatomy estimation

3D Point Cloud Visualization

Interactive 3D visualization for radiation therapy planning and analysis.

3D Viewer Preview

The 3D viewer is only available in the deployed environment.

To view the 3D model:

  1. Deploy this project to Vercel
  2. Ensure your GLB file is in the public directory
  3. Visit the deployed site to see your 3D model

About the Team

This research is led by Dr. David Thomas at the Thomas Lab, Jefferson Radiation Oncology. Our team includes experts in medical physics, computer science, and biomedical engineering.