Sequence optimization for MRI acoustic noise reduction

Yulin Wang, Pengfei Xu, Jie Zeng, Jichang Zhang, Yuliang Zhu, Shao Che, Chendie Yao, Yuwei Ge, Chengbo Wang

Research output: Journal PublicationConference articlepeer-review


The large acoustic noise of 80-110 dB during magnetic resonance imaging (MRI) scanning harms patients' comfort and health. The noise can be reduced by hardware modification or active noise control, but these methods are expensive, difficult, or not very effective. In this study, a sequence optimization method is used to mitigate the acoustic noise problem while maintaining image quality. The 4th order polynomial function is applied to design the new quiet pulse sequences, decreasing the gradient slew rate and higher time derivatives of the original trapezoidal lobes. A sound pressure level (SPL) estimation method is proposed to predict the acoustic noise loudness from the gradient and is used for genetic algorithm sequence optimization. The original and quiet gradient recalled echo (GRE) sequences are applied on a 1.5 T MRI scanner. The average SPL is reduced by 18.6 dBA, and the images show small differences and have similar SNR values. This method is also applied for the scouting and shimming GRE sequences in common clinical applications with significant noise reduction.

Original languageEnglish
Article number012034
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 2023
Event6th International Conference on Mechanical, Electric, and Industrial Engineering, MEIE 2023 - Sanya, China
Duration: 23 May 202325 May 2023

ASJC Scopus subject areas

  • Physics and Astronomy (all)


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