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提高言语产生的三维实时 MRI 成像质量。

Improved 3D real-time MRI of speech production.

机构信息

Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.

Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA.

出版信息

Magn Reson Med. 2021 Jun;85(6):3182-3195. doi: 10.1002/mrm.28651. Epub 2021 Jan 15.

Abstract

PURPOSE

To provide 3D real-time MRI of speech production with improved spatio-temporal sharpness using randomized, variable-density, stack-of-spiral sampling combined with a 3D spatio-temporally constrained reconstruction.

METHODS

We evaluated five candidate (k, t) sampling strategies using a previously proposed gradient-echo stack-of-spiral sequence and a 3D constrained reconstruction with spatial and temporal penalties. Regularization parameters were chosen by expert readers based on qualitative assessment. We experimentally determined the effect of spiral angle increment and k temporal order. The strategy yielding highest image quality was chosen as the proposed method. We evaluated the proposed and original 3D real-time MRI methods in 2 healthy subjects performing speech production tasks that invoke rapid movements of articulators seen in multiple planes, using interleaved 2D real-time MRI as the reference. We quantitatively evaluated tongue boundary sharpness in three locations at two speech rates.

RESULTS

The proposed data-sampling scheme uses a golden-angle spiral increment in the k -k plane and variable-density, randomized encoding along k . It provided a statistically significant improvement in tongue boundary sharpness score (P < .001) in the blade, body, and root of the tongue during normal and 1.5-times speeded speech. Qualitative improvements were substantial during natural speech tasks of alternating high, low tongue postures during vowels. The proposed method was also able to capture complex tongue shapes during fast alveolar consonant segments. Furthermore, the proposed scheme allows flexible retrospective selection of temporal resolution.

CONCLUSION

We have demonstrated improved 3D real-time MRI of speech production using randomized, variable-density, stack-of-spiral sampling with a 3D spatio-temporally constrained reconstruction.

摘要

目的

通过使用随机、变密度、螺旋堆叠采样与 3D 时空约束重建相结合,提供具有改进的时空锐度的言语产生的 3D 实时 MRI。

方法

我们使用先前提出的梯度回波螺旋堆叠序列和具有空间和时间约束的 3D 约束重建,评估了五种候选 (k, t) 采样策略。正则化参数由专家读者根据定性评估选择。我们通过实验确定了螺旋角增量和 k 时间顺序的影响。选择图像质量最高的策略作为提出的方法。我们在 2 名健康受试者中评估了提出的和原始的 3D 实时 MRI 方法,这些受试者执行了快速运动的言语产生任务,这些运动在多个平面上可见,使用交错的 2D 实时 MRI 作为参考。我们以两种言语速度在三个位置定量评估了舌边界的锐度。

结果

提出的数据采样方案在 k-k 平面中使用黄金角螺旋增量,并沿 k 进行变密度、随机编码。它在正常和 1.5 倍加速言语期间在舌的叶片、体部和根部提供了舌边界锐度评分的统计学显著提高 (P <.001)。在元音期间高、低舌位交替的自然言语任务中,定性改善非常显著。该方法还能够在快速的牙槽辅音段捕捉到复杂的舌形。此外,该方案允许灵活地回顾性选择时间分辨率。

结论

我们已经证明了使用随机、变密度、螺旋堆叠采样与 3D 时空约束重建相结合的言语产生的 3D 实时 MRI 的改进。

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