An Optimization-based Baseline for Rigid 2D/3D Registration Applied to Spine Surgical Navigation Using CMA-ES

TL;DR

This paper introduces a robust 2D/3D registration framework for spine surgical navigation using CMA-ES, enhancing accuracy and reliability in orthopedic surgery applications.

Contribution

It presents a coarse-to-fine registration method based on CMA-ES, demonstrating effectiveness on real clinical spine data and complementing existing AI-based approaches.

Findings

Effective registration on clinical spine data

High precision suitable for surgical navigation

Complementary to learning-based methods

Abstract

A robust and efficient optimization-based 2D/3D registration framework is crucial for the navigation system of orthopedic surgical robots. It can provide precise position information of surgical instruments and implants during surgery. While artificial intelligence technology has advanced rapidly in recent years, traditional optimization-based registration methods remain indispensable in the field of 2D/3D registration.he exceptional precision of this method enables it to be considered as a post-processing step of the learning-based methods, thereby offering a reliable assurance for registration. In this paper, we present a coarse-to-fine registration framework based on the CMA-ES algorithm. We conducted intensive testing of our method using data from different parts of the spine. The results shows the effectiveness of the proposed framework on real orthopedic spine surgery clinical data. This work can be viewed as an additional extension that complements the optimization-based methods employed in our previous studies.