A Study on High-Precision Localization of Facial Acupoints via Integrated 3D Surface Scanning and CT Image Fusion
Huan Yin, Sihan Sun, Yifei Pei, Shu Wang, Li Li, Junyan Tan, Ningbo Yu · 2025
This study presents a geometric 3D registration-based methodology for acupuncture point localization, specifically designed to enhance the precision of acupuncture treatment. The proposed approach integrates 3D surface scanning technology with internal CT imaging data, utilizing sophisticated 3D point cloud registration algorithms to achieve accurate localization of facial acupoints. In the experimental phase, comprehensive facial and whole-body CT datasets were acquired from two healthy volunteers using the 3D scanning and CT imaging equipment. The registration performance was rigorously evaluated through multiple quantitative metrics, including registration recall rate (RR), rotational error (RE), and translational error (TE). Comparative analysis against conventional maximal cliques (MAC) methods demonstrated the superior accuracy of our approach across standard benchmark datasets (3DMatch and KITTI). Experimental validation revealed that the localized facial acupoints exhibited exceptional alignment with physician-defined reference points, with minimal deviation well within clinical tolerance thresholds. These findings underscore the substantial potential of the proposed method in revolutionizing precise facial acupoint localization, thereby providing a groundbreaking technological framework to support and enhance traditional Chinese medicine acupuncture practice.