Research team

ARGOS - Augmented Reality-Guided Osteotomies for Surgery. 01/11/2025 - 31/10/2029

Abstract

In cancer resection, a millimetre can mean the difference between success and complications. Osteotomies demand high precision for proper bone alignment and healing. Traditional methods, such as physical cutting guides, are time-consuming, invasive, and costly, while freehand techniques are prone to errors. Augmented reality (AR) has emerged as a promising alternative, offering realtime intraoperative visualisation of the planned resections. However, existing AR systems struggle with tracking instabilities, occlusions, and lack of interactive guidance for surgeons, limiting clinical reliability. ARGOS develops a real-time, multi-modal AR guidance system for osteotomies, combining optical and inertial tracking with adaptive sensor fusion to improve system stability under dynamic surgical conditions. The system's resilience and accuracy will be evaluated under varying conditions through phantom-based experiments. A comparative study with surgeons will benchmark ARGOS against commonly used 3D-printed cutting guides, freehand techniques, and current AR passive guidance. Expected outcomes include up to 30 min reduction in surgical time, improved accuracy (<1.5 mm), and enhanced tracking robustness. Named after Argos Panoptes, the all-seeing giant of Greek mythology, ARGOS ensures continuous tracking despite surgical disturbances, bringing a new level of precision and confidence to osteotomies.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Integration of high-resolution MRI and micro-CT data. 01/10/1999 - 30/09/2001

Abstract

The main goal of this IWT-project is the development of a methodology to study an object with a high-resolution MRI and micro-CT system. This implies of course an optimization of the image information. Thus, a very important aspect of this project is the determination, optimization and comparison of the resolution of both imaging systems. Here the problem of resolution and reconstruction of CT and MRI will be studied with parameter estimation methods.

Researcher(s)

Research team(s)

    Project type(s)

    • Research Project