Synthetic Operating Room Table (SORT) Dataset

Project Period: 2019-2022

Abstract

This project focuses on the development of the Synthetic Operating Room Table (SORT) Dataset, designed to support research in medical robotics and surgical automation. The dataset provides synthetic data for training and evaluating robotic systems in operating room environments, addressing the critical need for high-quality training data in medical robotics applications.

The SORT dataset encompasses various scenarios and configurations that are commonly encountered in surgical settings, providing researchers with a comprehensive resource for developing and testing robotic systems designed for medical applications. This synthetic approach allows for controlled data generation while maintaining the complexity and variability required for robust system development.

Study Period: 2019-2022

Team Members: Roland Goecke; Damith Herath; Ibrahim Radwin; James Ireland