利用预测性降噪降低核磁共振成像中的声学噪声负担

Paulina Šiurytė, Sebastian Weingärtner
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引用次数: 0

摘要

尽管磁共振成像(MRI)检查每年每 100 名居民要做 16 次,但患者的舒适度和接受率却因暴露在巨大的声学噪声中而大打折扣。在这里,我们介绍一种利用从预测扫描仪声音中得出的抗噪声来消除声学噪声的系统。在这种被称为预测噪声消除(PNC)的方法中,核磁共振成像系统的声学指纹是在 60 秒的校准过程中获得的,并用于预测任意扫描程序的抗噪声。PNC 可在多种临床 MRI 序列中实现高达 13 分贝的声学噪声衰减,在 0.6 至 1.2 千赫之间的频谱噪声峰值衰减高达 96.76%。这些结果表明,预测扫描仪噪音可实现大量的孔内噪音消除,有望为改善患者舒适度提供一种廉价且独立于扫描仪的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lowering The Acoustic Noise Burden in MRI with Predictive Noise Canceling
Even though Magnetic Resonance Imaging (MRI) exams are performed up to 16 times per every 100 inhabitants each year, patient comfort and acceptance rates are strongly compromised by exposure to loud acoustic noise. Here we present a system for acoustic noise cancellation using anti-noise derived from predicted scanner sounds. In this approach, termed predictive noise canceling (PNC), the acoustic fingerprint of an MRI system is obtained during a 60 s calibration, and used to predict anti-noise for arbitrary scan procedures. PNC achieves acoustic noise attenuation of up to 13 dB across a wide range of clinical MRI sequences, with spectral noise peak reduction of up to 96.76 % occurring between 0.6 and 1.2 kHz. These results suggest that predicted scanner noise can achieve substantial in-bore noise cancellation with the prospect of providing a cheap and scanner-independent solution for improved patient comfort.
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