Inter-slice Super-resolution Based on Deformation Field and Grey Field Interpolation Networks

doi:10.3969/j.issn.1006-2475.2024.03.011

Abstract

Abstract:

Abstract： Magnetic resonance imaging is a widely used medical imaging method. Constrained by hardware conditions and other factors， the inter-slice resolution of MR images is much lower than the intra-slice resolution， resulting in low image quality and affecting the doctor’s diagnosis of the patient’s condition. Therefore， it is necessary to improve the inter-slice resolution to display more details of the image. In order to achieve super resolution between slices， an algorithm based on non-parametric deformation field and gray field interpolation network is proposed. Firstly， according to the principle of image registration， an approximate U-Net network is used for unsupervised training of two adjacent slices in low-resolution images to generate bidirectional deformation fields between slices. Then， the registered image is generated by using the first slice and the deformation field， and the registered image and the second slice are trained to obtain the bidirectional gray field between them， from which the deformation field and gray field at any position in the middle of the adjacent two slices can be obtained. Finally， any position slice in the middle can be obtained by interpolation method. Compared to other existing algorithms， this algorithm has significant improvement in visual effect and objective evaluation index， with PSNR and SSIM above 30 dB and 0.99， respectively.

Key words: Key words： magnetic resonance imaging, super-resolution, deformation field, grayscale field

CLC Number:

TP391

LIU Xun, ZHANG Dong, YUNG Da-long. Inter-slice Super-resolution Based on Deformation Field and Grey Field Interpolation Networks[J]. Computer and Modernization, 2024, 0(03): 67-71.

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