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A Reconfigurable Platform for Magnetic Resonance Data Acquisition and Processing.
IEEE Transactions on Medical Imaging ( IF 8.9 ) Pub Date : 2019-09-30 , DOI: 10.1109/tmi.2019.2944696
Josip Marjanovic , Jonas Reber , David O. Brunner , Maria Engel , Lars Kasper , Benjamin E. Dietrich , Laetitia Vionnet , Klaas P. Pruessmann

Developments in magnetic resonance imaging (MRI) in the last decades show a trend towards a growing number of array coils and an increasing use of a wide variety of sensors. Associated cabling and safety issues have been addressed by moving data acquisition closer to the coil. However, with the increasing number of radio-frequency (RF) channels and trend towards higher acquisition duty-cycles, the data amount is growing, which poses challenges for throughput and data handling. As it is becoming a limitation, early compression and preprocessing is becoming ever more important. Additionally, sensors deliver diverse data, which require distinct and often low-latency processing for run-time updates of scanner operation. To address these challenges, we propose the transition to reconfigurable hardware with an application tailored assembly of interfaces and real-time processing resources. We present an integrated solution based on a system-on-chip (SoC), which offers sufficient throughput and hardware-based parallel processing power for very challenging applications. It is equipped with fiber-optical modules serving as versatile interfaces for modular systems with in-field operation. We demonstrate the utility of the platform on the example of concurrent imaging and field sensing with hardware-based coil compression and trajectory extraction. The preprocessed data are then used in expanded encoding model based image reconstruction of single-shot and segmented spirals as used in time-series and anatomical imaging respectively.

中文翻译:

用于磁共振数据采集和处理的可重构平台。

过去几十年来,磁共振成像(MRI)的发展表明,阵列线圈的数量不断增加,并且各种传感器的使用也日益增多。通过将数据采集移到靠近线圈的位置,可以解决相关的布线和安全问题。但是,随着射频(RF)通道数量的增加和更高采集占空比的趋势,数据量正在增长,这对吞吐量和数据处理提出了挑战。随着它成为一种限制,早期压缩和预处理变得越来越重要。此外,传感器还提供各种数据,这些数据需要进行独特且通常为低延迟的处理,才能在运行时更新扫描仪操作。为了应对这些挑战,我们建议过渡到具有接口和实时处理资源的应用程序量身定制的可重配置硬件。我们提出了一种基于片上系统(SoC)的集成解决方案,该解决方案为极具挑战性的应用提供了足够的吞吐量和基于硬件的并行处理能力。它配备了光纤模块,可作为带有现场操作的模块化系统的多功能接口。我们在基于硬件的线圈压缩和轨迹提取的并发成像和场感测示例中演示了该平台的实用性。然后,将预处理后的数据用于分别基于时间序列和解剖成像的单次和分段螺旋的基于扩展编码模型的图像重建。我们提出了一种基于片上系统(SoC)的集成解决方案,该解决方案为极具挑战性的应用提供了足够的吞吐量和基于硬件的并行处理能力。它配备了光纤模块,可作为带有现场操作的模块化系统的多功能接口。我们在基于硬件的线圈压缩和轨迹提取的并发成像和场感测示例中演示了该平台的实用性。然后,将预处理后的数据用于分别基于时间序列和解剖成像的单次和分段螺旋的基于扩展编码模型的图像重建。我们提出了一种基于片上系统(SoC)的集成解决方案,该解决方案为极具挑战性的应用提供了足够的吞吐量和基于硬件的并行处理能力。它配备了光纤模块,可作为带有现场操作的模块化系统的多功能接口。我们在基于硬件的线圈压缩和轨迹提取的并发成像和场感测示例中演示了该平台的实用性。然后,将预处理后的数据用于分别基于时间序列和解剖成像的单次和分段螺旋的基于扩展编码模型的图像重建。它配备了光纤模块,可作为带有现场操作的模块化系统的多功能接口。我们在基于硬件的线圈压缩和轨迹提取的并发成像和场感测示例中演示了该平台的实用性。然后,将预处理后的数据用于分别基于时间序列和解剖成像的单次和分段螺旋的基于扩展编码模型的图像重建。它配备了光纤模块,可作为带有现场操作的模块化系统的多功能接口。我们在基于硬件的线圈压缩和轨迹提取的并发成像和场感测示例中演示了该平台的实用性。然后,将预处理后的数据用于分别基于时间序列和解剖成像的单次和分段螺旋的基于扩展编码模型的图像重建。
更新日期:2020-04-22
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