3D Pose Estimation of Epidural Catheter Markers based on a Single-View 2D X-ray Fluoroscopy

Minimal invasive surgery (MIS) requires precise control of flexible instruments to ensure safe and accurate procedures within complex anatomical structures. Accurate estimation of the three-dimensional (3D) pose of flexible surgical tools such as catheters is therefore crucial. While various sensing-based approaches, including fiber Bragg grating (FBG) sensors, electromagnetic (EM) tracking, and ultrasound localization, have been explored, these methods depend on additional sensing hardware and are sensitive to calibration and environmental conditions. X-ray imaging offers distinct advantages by allowing visualization without specialized catheters or external devices, enabling universal applicability; however, existing image-based tracking methods either rely on large training datasets, are limited to thick or structured catheters, or lack real-time performance. In this study, we present a slender-marker-based method to accurately estimate the 3D pose of a catheter from a single X-ray image using thin radiopaque marker sets compatible with commercially available epidural catheters. The proposed algorithm resolves the inherent 3D ambiguity in single-plane X-ray projections by combining a mixture-of-experts model with geometry-constrained refinement, and achieves real-time and precise tracking without any pre-obtained experimental data through simulation-based learning, enabling strong generalization across catheter types. Validation with X-ray and C-arm experiments confirmed clinically acceptable accuracy, below 2 mm, showing that the proposed approach preserves the advantages of X-ray–based interventions while reducing radiation exposure for both surgeons and patients.