Automatic evaluation of 3D registration quality in surgical navigation

Area of Science:

• Medical Imaging
• Computer-Assisted Surgery
• Surgical Navigation

Background:

• Surgical navigation systems require precise registration between pre-operative models and intraoperative data.
• Current methods for assessing registration quality are manual, post-registration, and time-consuming.
• There is a need for automated, real-time evaluation to improve surgical navigation accuracy and efficiency.

Purpose of the Study:

• To introduce a framework for automatic, real-time evaluation of 3D registration quality during the surgical navigation process.
• To enable continuous assessment of registration accuracy, aiding surgeons in determining the optimal time to conclude registration.
• To enhance surgeon confidence and improve the overall performance of surgical navigation systems.

Main Methods:

• A novel framework encodes 3D trajectories and registration hypotheses into structured heatmaps.
• A classification model analyzes these heatmaps for real-time evaluation of 3D registration quality.
• The framework is designed to be anatomy-agnostic, allowing generalization across various surgical procedures and anatomies.

Main Results:

• The framework was evaluated in video-based surgical navigation for anterior cruciate ligament reconstruction.
• It demonstrated robust, anatomy-agnostic registration quality evaluation, comparable to conventional methods.
• The system reduced intraoperative data digitization by an average of over 80%.

Conclusions:

• The developed framework facilitates automatic, real-time, and continuous assessment of 3D registration quality in surgical navigation.
• It supports surgeons throughout the registration process, potentially reducing procedure times and enhancing workflow efficiency.
• The framework's applicability extends beyond knee arthroscopy to other anatomies and surgical navigation procedures.