An automatic measurement method for ankle key angles based on point cloud segmentation network

Abstract

AbstractIn clinical practice, anterior distal tibialangle (ADTA) and lateral distal tibialangle (LDTA) are important evaluation indexes, which can reflect the degree of deformity and determine the type of deformity to a certain extent. The measurement process of these parameters involves the localization of multiple key regions. To simplify the process of measuring ADTA and LDTA, an automatic measurement method is proposed. First, this study constructs an ankle 3D point cloud dataset by 3D reconstruction of ankle electron computed tomography (CT) data, and then, an ankle point cloud segmentation network with a Self‐Attention mechanism and kernel point convolution combined with each other is constructed, and the ankle point cloud data with labels are input to this network to predict the ankle bone feature points. Finally, the segmented feature points are fitted, and the tibial backbone axis and distal tibial articular surface can be drawn, and based on the fitting results, ADTA and LDTA are obtained. Compared with manual measurements by physicians, the proposed method in this study achieved an average error of 0.46° with a passing rate of 97.7% for ADTA measurement. For LDTA measurement, the average error was 0.69° with a passing rate of 98%. The ankle joint key angle measurement system developed in this study meets the accuracy requirements of orthopedics and significantly reduces the workload for doctors.