Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal‐to‐noise ratio and speed of MRS

Background While magnetic resonance imaging (MRI) provides high resolution anatomical images with sharp soft tissue contrast, magnetic resonance spectroscopy (MRS) enables non‐invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal‐to‐noise ratio (SNR) when co...

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Bibliographic Details
Published in:	Medical physics (Lancaster) Vol. 50; no. 12; pp. 7955 - 7966
Main Authors:	Wang, Jing, Ji, Bing, Lei, Yang, Liu, Tian, Mao, Hui, Yang, Xiaofeng
Format:	Journal Article
Language:	English
Published:	United States 01.12.2023
Subjects:	Brain - diagnostic imaging Brain - metabolism denoising Humans Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging - methods Magnetic resonance spectroscopy (MRS) Magnetic Resonance Spectroscopy - methods metabolite quantification signal to noise ratio (SNR) Signal-To-Noise Ratio sparse representation stack auto‐encoder (SAE) denoising signal to noise ratio (SNR) metabolite quantification Magnetic resonance spectroscopy (MRS) sparse representation stack auto-encoder (SAE)
ISSN:	0094-2405, 2473-4209, 2473-4209
Online Access:	Get full text
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