Sparse Coding Super-Resolution Imaging for Enhancing Image Resolution in MRI

DOI
  • ISHIMARU Naoki
    Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University
  • OTA Junko
    National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology
  • UMEHARA Kensuke
    National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology
  • SUZUKI Takanori
    Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University
  • OHNO Shunsuke
    Osaka International Cancer Institute
  • OKAMOTO Kentaro
    Tenri Hospital
  • ISHIDA Takayuki
    Department of Medical Physics and Engineering, Graduate School of Medicine, Osaka University

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Other Title
  • MRI画像に対するスパースコーディング超解像処理の有用性

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Abstract

High-resolution medical images are desirable for practical application of high-resolution displays, however, it takes a long scanning time to improve image resolution in MRI. In this study, we applied and evaluated the sparse coding super-resolution (ScSR), which is one of the image processing techniques to obtain high-resolution images, for enhancing image resolution in MRI. For evaluation, T1-weighted images (T1), T2-weighted images (T2), fluid attenuated IR images (FLAIR), and time of flight images (TOF) were used as the test datasets. We up-sampled all images up to twice and compared the quality of the ScSR scheme and bilinear, bicubic, and lanczos interpolations, which are the traditional interpolation schemes. The image quality was evaluated by measuring peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). As a result, PSNR and SSIM of the ScSR were significantly higher (p<0.05) than those of other three interpolations in T1 (original and contrast-enhanced), T2 and FLAIR. In TOF, PSNR and SSIM of the ScSR were higher than those of other three interpolations for all images. These results suggest that the ScSR schemes markedly improve PSNR and SSIM in T1, T2, FLAIR and TOF, in comparison with the traditional interpolation schemes.

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