.png){kind=icon}
返回
MRI Denoising Using Pixel-Wise Threshold Selection
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2024.3449811.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Magnetic resonance imaging (MRI) has emerged as a promising technique for non-invasive medical imaging. The primary challenge in MRI is the trade-off between image visual quality and acquisition time. Current MRI image denoising algorithms employ global thresholding to denoise the whole image, which leads to inadequate denoising or image distortion. This study introduces a novel pixel-wise (localized) thresholding approach of singular vectors, obtained from singular value decomposition, to denoise magnetic resonance (MR) images. The pixel-wise thresholding of singular vectors is performed using separate singular values as thresholds at each pixel, which is advantageous given the spatial noise variation throughout the image. The method presented is validated on MR images of a standard phantom approved by the magnetic resonance accreditation program (MRAP). The denoised images display superior visual quality and recover minute structural information otherwise suppressed in the noisy image. The increase in peak-signal-to-noise-ratio (PSNR) and contrast-to-noise-ratio (CNR) values of >= 18% and >= 200% of the denoised images, respectively, imply efficient noise removal and visual quality enhancement. The structural similarity index (SSIM) of >= 0.95 for denoised images indicates that the crucial structural information is recovered through the presented method. A comparison with the standard filtering methods widely used for MRI denoising establishes the superior performance of the presented method. The presented pixel-wise denoising technique reduces the scan time by 2-3 times and has the potential to be integrated into any MRI system to obtain faster and better quality images.
Keyword:
Noise reduction
Magnetic resonance imaging
Vectors
Thresholding (Imaging)
Visualization
Pixel
Noise measurement
Biomedical imaging
denoising
image denoising
singular value decomposition
SF-SVD
pixel-wise noise threshold selection
pixel-wise thresholding
peak-signal-to-noise ratio
contrast-to-noise ratio
structural similarity index
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Effect of internal resistance of a Helmholtz resonator on acoustic energy reduction in enclosures
PREAI
分享收藏Hybrid SWOT Approach for Strategic Planning and Formulation in China Worldwide Express Mail Service
OAAI
OAAI分享收藏Efficient One-Pot Synthesis of 1,3-Disubstituted Pyridin-2(1H)-ones from α-HydroxyketeneS,S-Acetals under Vilsmeier Conditions.png)
Synthesis
SynthesisIF0
PREAI
分享收藏分享收藏
查看更多内容