MRI Acoustic Noise Prediction and Silent Sequence Optimization

Yulin Wang, Jie Zeng, Pengfei Xu, Jichang Zhang, Shiying Ke, Shengyang Niu, Yuliang Zhu, Shao Che, Chendie Yao, Chengbo Wang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

The large gradient switching-induced Lorentz forces can cause considerable acoustic noise, which is a disadvantage of magnetic resonance scanning, causing patient restlessness and safety risks. This sound should be characterized, predicted, evaluated, and reduced. In this study, the accurate gradient-to-acoustic noise transfer functions of x, y, and z axes gradient coils are measured with white noise input. Based on it, a 4th-order polynomial gradient smoothing function is proposed to reduce high-frequency components, and a genetic algorithm is employed to further optimize parameters to avoid resonance with the scanner. The example 2D gradient recalled echo sequence sound is decreased by 25.28 dBA (94.55%) and image quality is maintained with a negligible difference. This can be applied to various sequences to improve scanning comfort and reduce hearing harm.

Original languageEnglish
Title of host publicationBIBE 2024 - Conference Proceedings, 7th International Conference on Biological Information and Biomedical Engineering
EditorsXueli Chen
PublisherVDE Verlag GmbH
Pages16-20
Number of pages5
ISBN (Electronic)9783800762910
Publication statusPublished - 2024
Event7th International Conference on Biological Information and Biomedical Engineering, BIBE 2024 - Hybrid, Hohhot, China
Duration: 13 Aug 202415 Aug 2024

Publication series

NameBIBE 2024 - Conference Proceedings, 7th International Conference on Biological Information and Biomedical Engineering

Conference

Conference7th International Conference on Biological Information and Biomedical Engineering, BIBE 2024
Country/TerritoryChina
CityHybrid, Hohhot
Period13/08/2415/08/24

ASJC Scopus subject areas

  • Biotechnology
  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering

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