标题： 使用眼科超声视频自动测量视神经鞘直径 显示英文标题

标题： Automated Measurement of Optic Nerve Sheath Diameter Using Ocular Ultrasound Video

摘要： 目的。 颅内压（ICP）升高被认为是继发性脑损伤的生物标志物，视神经鞘直径（ONSD）与ICP之间存在显著的线性相关性。频繁监测ONSD可以有效支持ICP的动态评估。 然而，ONSD测量严重依赖操作者的经验和技能，尤其是在从超声序列中手动选择最佳帧并进行测量时。 方法。 本文提出了一种利用核相关滤波（KCF）跟踪算法和简单线性迭代聚类（SLIC）分割算法，自动识别视频序列中用于ONSD测量的最佳帧的新方法。通过高斯混合模型（GMM）结合基于KL散度的方法对视神经鞘进行映射和测量。 结果。 与两位专家医生的平均测量值相比，所提出的方法实现了0.04的平均误差、0.054的均方偏差以及0.782的组内相关系数（ICC）。 意义。 研究结果表明，该方法提供了高度准确的自动化ONSD测量，显示出临床应用的潜力。 显示英文摘要

摘要： Objective. Elevated intracranial pressure (ICP) is recognized as a biomarker of secondary brain injury, with a significant linear correlation observed between optic nerve sheath diameter (ONSD) and ICP. Frequent monitoring of ONSD could effectively support dynamic evaluation of ICP. However, ONSD measurement is heavily reliant on the operator's experience and skill, particularly in manually selecting the optimal frame from ultrasound sequences and measuring ONSD. Approach. This paper presents a novel method to automatically identify the optimal frame from video sequences for ONSD measurement by employing the Kernel Correlation Filter (KCF) tracking algorithm and Simple Linear Iterative Clustering (SLIC) segmentation algorithm. The optic nerve sheath is mapped and measured using a Gaussian Mixture Model (GMM) combined with a KL-divergence-based method. Results. When compared with the average measurements of two expert clinicians, the proposed method achieved a mean error, mean squared deviation, and intraclass correlation coefficient (ICC) of 0.04, 0.054, and 0.782, respectively. Significance. The findings suggest that this method provides highly accurate automated ONSD measurements, showing potential for clinical application.