Fast single image super-resolution using estimated low-frequency k-space data in MRI
Fast single image super-resolution using estimated low-frequency k-space data in MRI
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DOI：
10.1016/j.mri.2017.03.008
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发表时间：
2017-07-01
影响因子：
2.5
通讯作者：
Zhu, Yuemin
中科院分区：
文献类型：
--
作者：
Luo, Jianhua;Mou, Zhiying;Zhu, Yuemin
目的：单图像超分辨率（SR）在许多领域都是非常需要的，但在实践中获得它往往在技术上受到限制。本研究的目的是在磁共振成像（MRI）中提出一种简单、快速、鲁棒的单图像SR方法。方法：该思想基于给定（模数）低分辨率（LR）图像与期望的SR图像之间k空间内固有联系的数学公式。该方法分为两步：1)从单幅LR图像中估计所需SR图像的低频k空间数据；2)利用估计的低频和填充零的高频k空间数据重建SR图像。在数字幻像、物理幻像和真实脑MR图像上对该方法进行了评价，并与现有的磁共振成像方法进行了比较。结果：与现有的边缘引导非线性插值（EGNI）方法（PSNR=23.78dB， SSIM=0.983）、零填充（ZF）方法（PSNR=24.09dB， SSIM=0.985）和总变差（TV）方法（PSNR=24.54dB， SSIM=0.987）相比，所提出的SR方法在不同噪声水平下的PSNR （25.77dB）和SSIM（0.991）均有明显提高，且计算时间与ZF方法相同，但比EGNI或TV方法快得多。该方法在不同切片图像上的平均PSNR或SSIM （PSNR=26.33 dB或SSIM=0.955）也高于EGNI （PSNR=25.07dB或SSIM=0.952）、ZF （PSNR=24.97dB或SSIM=0.950）和TV （PSNR=25.70dB或SSIM=0.953）方法，表明该方法对图像解剖结构的变化具有较好的鲁棒性。同时，该方法产生的环状伪影比ZF方法少，图像比EGNI方法清晰，且不存在TV方法的遮挡效应。此外，在四种方法中，该方法的片间维空间一致性最高。结论：本研究通过从单幅空间模量LR图像中估计所需SR图像的低频k空间数据，提出了一种快速、鲁棒、高效的临床MR图像片间维空间一致性高的单幅SR方法。(C) 2017爱思唯尔公司版权所有。
Purpose: Single image super-resolution (SR) is highly desired in many fields but obtaining it is often technically limited in practice. The purpose of this study was to propose a simple, rapid and robust single image SR method in magnetic resonance (MR) imaging (MRI).Methods: The idea is based on the mathematical formulation of the intrinsic link in k-space between a given (modulus) low-resolution (LR) image and the desired SR image. The method consists of two steps: 1) estimating the low-frequency k-space data of the desired SR image from a single LR image; 2) reconstructing the SR image using the estimated low-frequency and zero-filled high-frequency k-space data. The method was evaluated on digital phantom images, physical phantom MR images and real brain MR images, and compared with existing SR methods.Results: The proposed SR method exhibited a good robustness by reaching a clearly higher PSNR (25.77dB) and SSIM (0.991) averaged over different noise levels in comparison with existing edge-guided nonlinear interpolation (EGNI) (PSNR=23.78dB, SSIM=0.983), zero-filling (ZF) (PSNR=24.09dB, SSIM=0.985) and total variation (TV) (PSNR=24.54dB, SSIM=0.987) methods while presenting the same order of computation time as the ZF method but being much faster than the EGNI or TV method. The average PSNR or SSIM over different slice images of the proposed method (PSNR=26.33 dB or SSIM=0.955) was also higher than the EGNI (PSNR=25.07dB or SSIM=0.952), ZF (PSNR=24.97dB or SSIM=0.950) and TV (PSNR=25.70dB or SSIM=0.953) methods, demonstrating its good robustness to variation in anatomical structure of the images. Meanwhile, the proposed method always produced less ringing artifacts than the ZF method, gave a clearer image than the EGNI method, and did not exhibit any blocking effect presented in the TV method. In addition, the proposed method yielded the highest spatial consistency in the inter-slice dimension among the four methods.Conclusions: This study proposed a fast, robust and efficient single image SR method with high spatial consistency in the inter-slice dimension for clinical MR images by estimating the low-frequency k-space data of the desired SR image from a single spatial modulus LR image. (C) 2017 Elsevier Inc. All rights reserved.