Lowering The Acoustic Noise Burden in MRI with Predictive Noise Canceling

Abstract

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.