Flexible Alignment Super-Resolution Network for Multi-Contrast MRI

10/07/2022
by   Yiming Liu, et al.
0

Magnetic resonance images play an essential role in clinical diagnosis by acquiring the structural information of biological tissue. However, during acquiring magnetic resonance images, patients have to endure physical and psychological discomfort, including irritating noise and acute anxiety. To make the patient feel cozier, technically, it will reduce the retention time that patients stay in the strong magnetic field at the expense of image quality. Therefore, Super-Resolution plays a crucial role in preprocessing the low-resolution images for more precise medical analysis. In this paper, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast magnetic resonance images Super-Resolution. The core of multi-contrast SR is to match the patches of low-resolution and reference images. However, the inappropriate foreground scale and patch size of multi-contrast MRI sometimes lead to the mismatch of patches. To tackle this problem, the Flexible Alignment module is proposed to endow receptive fields with flexibility. Flexible Alignment module contains two parts: (1) The Single-Multi Pyramid Alignmet module serves for low-resolution and reference image with different scale. (2) The Multi-Multi Pyramid Alignment module serves for low-resolution and reference image with the same scale. Extensive experiments on the IXI and FastMRI datasets demonstrate that the FASR-Net outperforms the existing state-of-the-art approaches. In addition, by comparing the reconstructed images with the counterparts obtained by the existing algorithms, our method could retain more textural details by leveraging multi-contrast images.

READ FULL TEXT

page 1

page 2

page 4

page 8

page 9

research
08/05/2019

Multi-Contrast Super-Resolution MRI Through a Progressive Network

Magnetic resonance imaging (MRI) is widely used for screening, diagnosis...
research
05/19/2021

Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network

Super-resolution (SR) plays a crucial role in improving the image qualit...
research
07/05/2023

Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRI

Limited by imaging systems, the reconstruction of Magnetic Resonance Ima...
research
06/17/2022

Multi-scale Super-resolution Magnetic Resonance Spectroscopic Imaging with Adjustable Sharpness

Magnetic Resonance Spectroscopic Imaging (MRSI) is a valuable tool for s...
research
07/05/2023

Compound Attention and Neighbor Matching Network for Multi-contrast MRI Super-resolution

Multi-contrast magnetic resonance imaging (MRI) reflects information abo...
research
02/21/2020

3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution

Magnetic resonance imaging (MRI) enables plant scientists to non-invasiv...
research
09/03/2021

Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution

Super-resolving the Magnetic Resonance (MR) image of a target contrast u...

Please sign up or login with your details

Forgot password? Click here to reset