High-speed Registration between 3D and 2D Point Clouds Using Geometric Analysis of Blood Vessel Cross-sections in Ultrasound Images

This study aimed to develop a high-precision and high-speed registration method to support clinicians during minimally invasive therapies such as high-intensity focused ultrasound (HIFU) therapy. In these procedures, accurate localization and treatment of pathological regions within a restricted surgical field require a high level of expertise. Therefore, real-time and highly accurate intraoperative navigation is essential. To address this need, we proposed a method of extracting blood vessel cross-sections from intraoperative ultrasound images, quantifying their planar dispersion and structural complexity, and investigating geometric parameters that contribute to improved registration accuracy. Additionally, we examined suitable point cloud generation methods for point-based registration to enhance real-time performance. The feasibility of the proposed method was further validated under simulated clinical condition such as natural respiration. Our method achieved the HIFU-required accuracy of less than 5 mm and demonstrated processing within 0.2 seconds, which is significantly faster than conventional approaches. These findings suggest the potential applicability of our method as a surgeon assistant system in ultrasound-guided therapy.