Accurate Magnetic Resonance Image Super-Resolution Using Deep Networks and Gaussian Filtering in the Stationary Wavelet Domain

Accurate Magnetic Resonance Image Super-Resolution Using Deep Networks and Gaussian Filtering in the Stationary Wavelet Domain

In this correspondence, we present an accurate Magnetic Resonance (MR) image Super-Resolution (SR) method that uses a Very Deep Residual network (VDR-net) in the training phase. By applying 2D Stationary Wavelet Transform (SWT), we decompose each Low Resolution (LR)-High Resolution (HR) example imag...

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Bibliographic Details
Main Authors: Gunnam Suryanarayana, Karthik Chandran, Osamah Ibrahim Khalaf, Youseef Alotaibi, Abdulmajeed Alsufyani, Saleh Ahmed Alghamdi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning
edge-preservation
MR imaging
residual network
stationary wavelet decomposition
super-resolution
Online Access:https://ieeexplore.ieee.org/document/9423994/

Internet

https://ieeexplore.ieee.org/document/9423994/

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