Ji Yuqi, Huang Tianqi, Wu Yutong, Li Ruiyang, Wang Pengfei, Dong Jiahong, Liao Honegen
School of Biomedical Engineering, Tsinghua University, Beijing, China.
School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
Int J Comput Assist Radiol Surg. 2025 Mar;20(3):613-623. doi: 10.1007/s11548-024-03273-1. Epub 2024 Oct 14.
Ultrasound serves as a crucial intraoperative imaging tool for hepatobiliary surgeons, enabling the identification of complex anatomical structures like blood vessels, bile ducts, and lesions. However, the reliance on manual mental reconstruction of 3D topologies from 2D ultrasound images presents significant challenges, leading to a pressing need for tools to assist surgeons with real-time identification of 3D topological anatomy.
We propose a real-time ultrasound AR 3D visualization method for intraoperative 2D ultrasound imaging. Our system leverages backward alpha blending to integrate multi-planar ultrasound data effectively. To ensure continuity between 2D ultrasound planes, we employ spatial smoothing techniques to interpolate the widely spaced ultrasound planes. A dynamic 3D transfer function is also developed to enhance spatial representation through color differentiation.
Comparative experiments involving our AR visualization of 3D ultrasound, alongside AR visualization of 2D ultrasound and 2D visualization of 3D ultrasound, demonstrated that the proposed method significantly reduced operational time(110.25 ± 27.83 s compared to 292 ± 146.63 s and 365.25 ± 131.62 s), improved depth perception and comprehension of complex topologies, contributing to reduced pressure and increased personal satisfaction among users.
Quantitative experimental results and feedback from both novice and experienced physicians highlight our system's exceptional ability to enhance the understanding of complex topological anatomy. This improvement is crucial for accurate ultrasound diagnosis and informed surgical decision-making, underscoring the system's clinical applicability.
超声是肝胆外科医生重要的术中成像工具,能够识别血管、胆管和病变等复杂解剖结构。然而,从二维超声图像手动在脑海中重建三维拓扑结构存在重大挑战,因此迫切需要工具来协助外科医生实时识别三维拓扑解剖结构。
我们提出一种用于术中二维超声成像的实时超声增强现实三维可视化方法。我们的系统利用反向阿尔法混合有效地整合多平面超声数据。为确保二维超声平面之间的连续性,我们采用空间平滑技术对间隔较大的超声平面进行插值。还开发了一种动态三维传递函数,通过颜色区分来增强空间表示。
涉及我们的三维超声增强现实可视化、二维超声增强现实可视化和三维超声二维可视化的对比实验表明,所提出的方法显著减少了操作时间(分别为110.25±27.83秒,而另外两种方法分别为292±146.63秒和365.25±131.62秒),改善了对复杂拓扑结构的深度感知和理解,有助于减轻用户压力并提高个人满意度。
新手和经验丰富医生的定量实验结果及反馈突出了我们系统在增强对复杂拓扑解剖结构理解方面的卓越能力。这种改进对于准确的超声诊断和明智的手术决策至关重要,强调了该系统的临床适用性。