基于细节增强的MR序列转换方法

doi:10.11959/j.issn.2096-6652.202110

Abstract

Abstract:

Magnetic resonance (MR) is a widely used medical imaging method.However, MR images of certain modalities are not easy to obtain directly and thus need to be converted from other modality.To solve these problem, a conversion method of MR sequence based on detail enhancement was proposed.The proposed method constructed an end-to-end network with two conditional GAN-based modules: resiguals template generation module (ResGAN) and detail enhancement module (EnGAN).The proposed method are tested on a set of registered neurofibroma T1 and STIR images, which demonstrate that the proposed method can restore boundary details and signal intensity details better than other existing methods.

Key words: cross-modality magnetic resonance, generative adversarial network, medical image processing

CLC Number:

R445.2

Fan YAN, Yining DI, Jianwei ZHANG, et al. Conversion method of magnetic resonance sequence based on detail enhancement[J]. Chinese Journal of Intelligent Science and Technology, 2021, 3(1): 93-100.

Figures/Tables 10

方法	SSIM	PSNR	MSE
Pix2Pix	0.785 5	17.209 1	0.004 9
VAE	$0 . 8124$	$18 . 1298$	$0 . 0041$
Ea-GAN	0.789	16.977 9	0.005 2
本文提出的方法	0.798 8	17.357 7	0.004 8

方法	SSIM	PSNR	MSE
without edge loss	0.791 3	16.952 6	0.005 3
without res loss	0.792 8	17.193 3	0.005
本文提出的方法	$0 . 7988$	$17 . 3577$	$0 . 0048$

References 26

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