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基于图谱的舌肌相关性分析:来自标记和高分辨率磁共振成像。

Atlas-Based Tongue Muscle Correlation Analysis From Tagged and High-Resolution Magnetic Resonance Imaging.

机构信息

Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston.

Department of Neural and Pain Sciences, University of Maryland Dental School, Baltimore.

出版信息

J Speech Lang Hear Res. 2019 Jul 15;62(7):2258-2269. doi: 10.1044/2019_JSLHR-S-18-0495. Epub 2019 Jul 2.

Abstract

Purpose Intrinsic and extrinsic tongue muscles in healthy and diseased populations vary both in their intra- and intersubject behaviors during speech. Identifying coordination patterns among various tongue muscles can provide insights into speech motor control and help in developing new therapeutic and rehabilitative strategies. Method We present a method to analyze multisubject tongue muscle correlation using motion patterns in speech sound production. Motion of muscles is captured using tagged magnetic resonance imaging and computed using a phase-based deformation extraction algorithm. After being assembled in a common atlas space, motions from multiple subjects are extracted at each individual muscle location based on a manually labeled mask using high-resolution magnetic resonance imaging and a vocal tract atlas. Motion correlation between each muscle pair is computed within each labeled region. The analysis is performed on a population of 16 control subjects and 3 post-partial glossectomy patients. Results The floor-of-mouth (FOM) muscles show reduced correlation comparing to the internal tongue muscles. Patients present a higher amount of overall correlation between all muscles and exercise en bloc movements. Conclusions Correlation matrices in the atlas space show the coordination of tongue muscles in speech sound production. The FOM muscles are weakly correlated with the internal tongue muscles. Patients tend to use FOM muscles more than controls to compensate for their postsurgery function loss.

摘要

目的

健康人群和患病人群的固有和外在舌肌在言语过程中的内、主体间行为均存在差异。识别各种舌肌之间的协调模式可以深入了解言语运动控制,并有助于开发新的治疗和康复策略。

方法

我们提出了一种使用语音产生中的运动模式来分析多主体舌肌相关性的方法。使用标记的磁共振成像(MRI)捕捉肌肉运动,并使用基于相位的变形提取算法进行计算。在组装到公共图谱空间后,基于高分辨率 MRI 和声道图谱在每个个体肌肉位置上使用手动标记的掩模提取多个主体的运动。在每个标记区域内计算每对肌肉之间的运动相关性。对 16 名对照受试者和 3 名部分舌切除术患者进行了分析。

结果

与内部舌肌相比,口腔底部(FOM)肌肉的相关性降低。与对照组相比,患者的所有肌肉之间的总体相关性更高,并且可以整体协调运动。

结论

图谱空间中的相关矩阵显示了言语产生过程中舌肌的协调情况。FOM 肌肉与内部舌肌的相关性较弱。与对照组相比,患者更倾向于使用 FOM 肌肉来补偿术后功能丧失。

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