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具有联合低秩和稀疏约束的高分辨率动态语音成像

High-resolution dynamic speech imaging with joint low-rank and sparsity constraints.

作者信息

Fu Maojing, Zhao Bo, Carignan Christopher, Shosted Ryan K, Perry Jamie L, Kuehn David P, Liang Zhi-Pei, Sutton Bradley P

机构信息

Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA; Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.

出版信息

Magn Reson Med. 2015 May;73(5):1820-32. doi: 10.1002/mrm.25302. Epub 2014 Jun 9.

DOI:10.1002/mrm.25302
PMID:24912452
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4261062/
Abstract

PURPOSE

To enable dynamic speech imaging with high spatiotemporal resolution and full-vocal-tract spatial coverage, leveraging recent advances in sparse sampling.

METHODS

An imaging method is developed to enable high-speed dynamic speech imaging exploiting low-rank and sparsity of the dynamic images of articulatory motion during speech. The proposed method includes: (a) a novel data acquisition strategy that collects spiral navigators with high temporal frame rate and (b) an image reconstruction method that derives temporal subspaces from navigators and reconstructs high-resolution images from sparsely sampled data with joint low-rank and sparsity constraints.

RESULTS

The proposed method has been systematically evaluated and validated through several dynamic speech experiments. A nominal imaging speed of 102 frames per second (fps) was achieved for a single-slice imaging protocol with a spatial resolution of 2.2 × 2.2 × 6.5 mm(3) . An eight-slice imaging protocol covering the entire vocal tract achieved a nominal imaging speed of 12.8 fps with the identical spatial resolution. The effectiveness of the proposed method and its practical utility was also demonstrated in a phonetic investigation.

CONCLUSION

High spatiotemporal resolution with full-vocal-tract spatial coverage can be achieved for dynamic speech imaging experiments with low-rank and sparsity constraints.

摘要

目的

利用稀疏采样的最新进展,实现具有高时空分辨率和全声道空间覆盖的动态语音成像。

方法

开发了一种成像方法,以利用语音过程中发音运动动态图像的低秩和稀疏性实现高速动态语音成像。所提出的方法包括:(a)一种新颖的数据采集策略,该策略以高时间帧率采集螺旋导航器;(b)一种图像重建方法,该方法从导航器中导出时间子空间,并利用联合低秩和稀疏约束从稀疏采样数据中重建高分辨率图像。

结果

通过多个动态语音实验对所提出的方法进行了系统评估和验证。对于空间分辨率为2.2×2.2×6.5 mm³的单层成像协议,实现了标称每秒102帧(fps)的成像速度。覆盖整个声道的八层成像协议在相同空间分辨率下实现了标称每秒12.8帧的成像速度。在语音研究中也证明了所提出方法的有效性及其实际效用。

结论

对于具有低秩和稀疏约束的动态语音成像实验,可以实现具有全声道空间覆盖的高时空分辨率。

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High-resolution cardiovascular MRI by integrating parallel imaging with low-rank and sparse modeling.基于低秩稀疏模型的并行成像技术在心血管磁共振中的应用
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