Three-dimensional (3D) Ultrasound (US) can facilitate diagnosis, treatment planning, and image-guided therapy. However, current studies rarely provide a comprehensive evaluation of volumetric accuracy and reproducibility, highlighting the need for robust Quality Assurance (QA) frameworks, particularly for tracked 3D US reconstruction using freehand or robotic acquisition. This study presents a QA framework for 3D US reconstruction and a flexible open source platform for tracked US research. A custom phantom containing geometric inclusions with varying symmetry properties enables straightforward evaluation of optical, electromagnetic, and robotic kinematic tracking for 3D US at different scanning speeds and insonation angles. A standardised pipeline performs real-time segmentation and 3D reconstruction of geometric targets (DSC = 0.97, FPS = 46) without GPU acceleration, followed by automated registration and comparison with ground-truth geometries. Applying this framework showed that our robotic 3D US achieves state-of-the-art reconstruction performance (DSC-3D = 0.94 +- 0.01, HD95 = 1.17 +- 0.12), approaching the spatial resolution limit imposed by the transducer. This work establishes a flexible experimental platform and a reproducible validation methodology for 3D US reconstruction. The proposed framework enables robust cross-platform comparisons and improved reporting practices, supporting the safe and effective clinical translation of 3D ultrasound in diagnostic and image-guided therapy applications.

翻译：三维（3D）超声可促进诊断、治疗规划及图像引导治疗。然而，当前研究鲜少提供对体积准确性与可重复性的全面评估，凸显了对稳健质量保证框架的需求，尤其对于采用徒手或机器人采集的跟踪3D超声重建。本研究提出一个面向3D超声重建的质量保证框架，以及一个用于跟踪超声研究的灵活开源平台。包含具有不同对称特性的几何包容体的定制体模，能够在不同扫描速度和入射角下，直接评估3D超声的光学、电磁及机器人运动学跟踪效果。标准化流程可在无需GPU加速的情况下，实时分割并重建几何目标（DSC=0.97，FPS=46），随后进行自动配准并与真实几何结构对比。应用该框架表明，我们的机器人3D超声达到了当前最优的重建性能（DSC-3D=0.94±0.01，HD95=1.17±0.12），接近换能器所限的空间分辨率极限。本研究为3D超声重建建立了一个灵活的实验平台与可复现的验证方法。所提框架能够实现稳健的跨平台比较，并改进报告实践，从而支持三维超声在诊断与图像引导治疗应用中安全、有效的临床转化。