A Modified Higher-Order Singular Value Decomposition Framework With Adaptive Multilinear Tensor Rank Approximation for Three-Dimensional Magnetic Resonance Rician Noise Removal

A Modified Higher-Order Singular Value Decomposition Framework With Adaptive Multilinear Tensor Rank Approximation for Three-Dimensional Magnetic Resonance Rician Noise Removal

The magnetic resonance (MR) images are acknowledged to be inevitably corrupted by Rician distributed noise, which adversely affected the image quality for diagnosis purpose. However, the traditional denoising methods may recover the images from corruptions with severe loss of detailed structure and...

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Bibliographic Details
Main Authors: Li Wang, Di Xiao, Wen S. Hou, Xiao Y. Wu, Lin Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Oncology
Subjects:
HOSVD
logarithm function
low rank tensor approximation
Rician noise
magnetic resonance images
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2020.01640/full

Internet

https://www.frontiersin.org/article/10.3389/fonc.2020.01640/full

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