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The Active Control Technique Of MRI Scanning Noise

Posted on:2019-01-02Degree:MasterType:Thesis
Country:ChinaCandidate:X J LiuFull Text:PDF
GTID:2394330566460588Subject:Radio Physics
Abstract/Summary:PDF Full Text Request
Compared with CT scanning,ultrasonic inspection and other medical examination means,magnetic resonance imaging technique has higher qualitative diagnostic accuracy,which can be used to detect different body tissues and organs without any harmful radiation for human body.However,the noise is up to about 130 dB(A)in the magnetic resonance imaging system during the process of scanning.When patients receipt the noise,it maybe damage their hearing and has some negative effects(such as anxiety,hearing disorder)on them.In order to reduce the intensity of the noise they received in the process of scanning,the operator will ask patients wear earplugs,ear cover and other acoustic components.The high frequency noise is effectively reduced by those equipment which is hardly to control the low frequency noise.In recent years,active noise control(ANC)technology can settle the problem with the development of digital processing technology and adaptive filtering technology.Based on the theory of adaptive filter in signal processing,we mainly studied the key technologies of implementing adaptive active noise control system,including Fx LMS algorithm,secondary path modeling and hardware implementation of adaptive active noise control.In addition,based on the active noise control feed-forward control system,this paper proposes a new noise reduction system,namely the quasi-feedforward control system.Because NI USB-7856 R is equipped with LabVIEW FPGA,which has lots of advantages,such as repeatable configuration,real-time operation,fast speed and easy to develop,etc.Therefore,combined with the simulation platform LabVIEW software,NI USB-7856 R equipment is used for setting up a magnetic resonance noise active control simulation program.
Keywords/Search Tags:Magnetic resonance imaging(MRI), Active noise control technology, Quasi-feedforward control system, Secondary path modeling, FxLMS algorithm
PDF Full Text Request
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