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声门边缘的经验分布(EDGE):使用高速视频内窥镜对声带运动学的统计评估。

Empirical Distribution of Glottal Edges (EDGE): A Statistical Assessment of Vocal Fold Kinematics Using High-Speed Videoendoscopy.

作者信息

Ibarra Emiro J, Galindo Gabriel E, Alzamendi Gabriel A, Cortes Juan P, Castro Christian, Manriquez Rodrigo, Testart Alba, Zanartu Matias

出版信息

IEEE J Biomed Health Inform. 2025 Feb;29(2):1087-1100. doi: 10.1109/JBHI.2024.3462632. Epub 2025 Feb 10.

DOI:10.1109/JBHI.2024.3462632
PMID:39288042
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12094672/
Abstract

Although laryngeal high-speed videoendoscopy (HSV) is crucial for studying vocal fold vibrations, its translation to clinical practice has been hindered by the large volume of data it produces and the difficulty in interpreting current analysis methods. Although image processing techniques have been developed to map spatial-temporal data into two-dimensional representations, they alter the geometrical construction of the glottis and do not provide standard quantitative features, thus challenging clinical interpretation. In response, we propose a new visualization and analysis framework for assessing the dynamics of vocal folds based on the empirical distribution of the glottal edge using HSV. This procedure analyzes vocal fold oscillations by preserving the shape of the glottis and quantifying the asymmetry between right and left vocal fold displacements along the anterior-posterior axis. This method was evaluated on four groups of participants: ten with normal voices, ten with vocal fold nodules, ten with muscle tension dysphonia, and two with unilateral vocal fold paralysis. The proposed method produces distinct representations for normal and pathological vocal fold vibratory behaviors and derived features based on amplitude and phase asymmetry metrics that show statistically significant differences between normal and pathological groups. Comparative analysis with state-of-the-art techniques indicates that our proposed method can complement the assessment of vocal fold vibration and enhance the clinical translation of HSV.

摘要

尽管喉高速视频内镜检查(HSV)对于研究声带振动至关重要,但其在临床实践中的应用却受到其产生的大量数据以及当前分析方法难以解读的阻碍。尽管已经开发了图像处理技术将时空数据映射为二维表示,但这些技术改变了声门的几何结构,并且没有提供标准的定量特征,从而给临床解读带来了挑战。作为回应,我们提出了一种新的可视化和分析框架,用于基于HSV使用声门边缘的经验分布来评估声带的动态变化。该程序通过保留声门形状并量化左右声带沿前后轴位移之间的不对称性来分析声带振荡。该方法在四组参与者中进行了评估:十名嗓音正常者、十名有声带小结者、十名有肌肉紧张性发声障碍者以及两名单侧声带麻痹者。所提出的方法针对正常和病理性声带振动行为产生了独特的表示,并基于幅度和相位不对称度量得出了特征,这些特征在正常组和病理组之间显示出统计学上的显著差异。与现有技术的对比分析表明,我们提出的方法可以补充声带振动评估,并增强HSV在临床中的应用。

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本文引用的文献

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Re-Training of Convolutional Neural Networks for Glottis Segmentation in Endoscopic High-Speed Videos.用于内镜高速视频中声门分割的卷积神经网络再训练
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