Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Emmanuel Le Clézio
University of Montpellier
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Attention gated encoder-decoder for ultrasonic signal denoising Nabil Jai Mansouri; Ghizlane Khaissidi; Gilles Despaux; Mostafa Mrabti; Emmanuel Le Clézio
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1695-1703

Abstract

Ultrasound imaging is one of the most widely used non-destructive testingmethods. The transducer emits pulses that travel through the imaged samplesand are reflected by echo-forming impedance. The resulting ultrasonic signalsusually contain noise. Most of the traditional noise reduction algorithmsrequire high skills and prior knowledge of noise distribution, which has acrucial impact on their performances. As a result, these methods generallyyield a loss of information, significantly influencing the final data and deeplylimiting both sensitivity and resolution of imaging devices in medical andindustrial applications. In the present study, a denoising method based on anattention-gated convolutional autoencoder is proposed to fill this gap. Toevaluate its performance, the suggested protocol is compared to widely usedmethods such as butterworth filtering (BF), discrete wavelet transforms(DWT), principal component analysis (PCA), and convolutional autoencoder(CAE) methods. Results proved that better denoising can be achievedespecially when the original signal-to-noise ratio (SNR) is very low and thesound waves’ traces are distorted by noise. Moreover, the initial SNR wasimproved by up to 30 dB and the resulting Pearson correlation coefficient wasmaintained over 99% even for ultrasonic signals with poor initial SNR.
Co-Authors Ghizlane Khaissidi Gilles Despaux Mostafa Mrabti Nabil Jai Mansouri