# An Augmented Reality-Based Navigation System for Stereotactic Brain Biopsy with Multi-Objective Path Planning and Hybrid Registration

## TL;DR

This paper introduces an augmented reality system for brain biopsies that improves safety and efficiency through automated path planning and accurate real-time navigation.

## Contribution

A hybrid registration strategy combining QR codes and anatomical landmarks for AR alignment, and a safety-focused multi-objective optimization model for path planning.

## Key findings

- The MOO model outperformed manual methods in meeting safety criteria for brain tumor biopsies.
- Hybrid registration reduced fiducial registration error significantly compared to conventional methods.
- The system achieved a mean clinical setup time of 2.63 minutes with high accuracy.

## Abstract

What are the main findings?
A safety-oriented multi-objective optimization model enables automated and clinically compliant biopsy path planning.A hybrid registration strategy combining QR codes and anatomical landmarks achieves accurate augmented reality alignment with rapid clinical setup.

A safety-oriented multi-objective optimization model enables automated and clinically compliant biopsy path planning.

A hybrid registration strategy combining QR codes and anatomical landmarks achieves accurate augmented reality alignment with rapid clinical setup.

What are the implications of the main findings?
Explicitly embedding clinical constraints into automated path planning reduces reliance on manual decision-making during preoperative surgical planning.Intuitive, real-time three-dimensional overlays of anatomical structures and planned paths can reduce surgeons’ cognitive load in intraoperative neuronavigation.

Explicitly embedding clinical constraints into automated path planning reduces reliance on manual decision-making during preoperative surgical planning.

Intuitive, real-time three-dimensional overlays of anatomical structures and planned paths can reduce surgeons’ cognitive load in intraoperative neuronavigation.

Background: Stereotactic brain biopsy is the gold standard for the pathological diagnosis of malignant brain tumors. However, conventional procedures rely heavily on manual path planning and unintuitive navigation, which significantly increase the risk of severe complications and impose an additional cognitive burden on surgeons. Methods: We propose an augmented reality-based navigation system that synergizes multi-objective path planning with hybrid registration. Preoperatively, the system utilizes a constrained multi-objective optimization (MOO) model derived from clinical criteria to automatically calculate and visualize optimal biopsy paths within a three-dimensional anatomical environment. Intraoperatively, the system performs rapid initial alignment using quick response (QR) codes, followed by precise refinement through anatomical landmarks. This process ultimately enables the highly accurate, real-time overlay of the surgical path and anatomical models onto the patient’s operative field. Results: An expert study across four common brain tumor locations demonstrated that the MOO model significantly outperformed manual methods in satisfying safety criteria. The hybrid registration reduced the mean fiducial registration error (FRE) from 4.19 ± 1.11 mm to 2.37 ± 0.91 mm (p < 0.001), with a mean target registration error (TRE) of 2.34 ± 0.71 mm and a mean clinical setup time of 2.63 ± 0.36 min. Conclusions: This system assists stereotactic brain biopsy through automated path planning and immersive augmented reality-based guidance, highlighting its potential to support surgical workflow consistency and procedural safety.