Contour-based Bone Axis Detection for X-Ray Guided Surgery on the Knee

TL;DR

This paper presents an automatic, learning-based method for detecting the anatomical axis of long bones in X-ray images, aiding surgical procedures with high accuracy and reliability.

Contribution

It introduces a novel contour-based approach translating the two-line method into a learning framework for bone axis detection.

Findings

Median angulation error of 0.19° for femoral bones

Median angulation error of 0.33° for tibial bones

Confirmed reliability through expert inter-rater study

Abstract

The anatomical axis of long bones is an important reference line for guiding fracture reduction and assisting in the correct placement of guide pins, screws, and implants in orthopedics and trauma surgery. This study investigates an automatic approach for detection of such axes on X-ray images based on the segmentation contour of the bone. For this purpose, we use the medically established two-line method and translate it into a learning-based approach. The proposed method is evaluated on 38 clinical test images of the femoral and tibial bone and achieves a median angulation error of 0.19{\deg} and 0.33{\deg} respectively. An inter-rater study with three trauma surgery experts confirms reliability of the method and recommends further clinical application.