Three-Dimensional Needle Tip Estimation from Multi-View X-Ray Images for Interventional Pain Procedures

Abstract

This study addresses the challenge of estimating the three-dimensional(3D) position of a needle tip from two-dimensional(2D) X-ray images. We propose a classical image processing–based framework for needle tip localization and 3D reconstruction. The method first detects a circular marker attached to the robotic end-effector that controls the needle insertion and identifies the needle head position within the marker. Preprocessing steps, including bilateral filtering, thresholding, and iterative morphological operations, are applied to improve image quality and ensure the continuity of the needle shaft. A flood-fill algorithm is then used to segment the needle body, after which the needle trajectory is extracted using the A^star algorithm. Finally, the 3D position of the needle tip is reconstructed by Triangulation from multiple X-ray images acquired at different viewing angles.