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Non‑local diffusion‑weighted image super‑resolution using collaborative joint information

  • Authors:
    • Zhipeng Yang
    • Peiyu He
    • Jiliu Zhou
    • Xi Wu
  • View Affiliations / Copyright

    Affiliations: School of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan 610065, P.R. China, Department of Computer Science, Chengdu University of Information Technology, Chengdu, Sichuan 610225, P.R. China
    Copyright: © Yang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 217-225
    |
    Published online on: November 1, 2017
       https://doi.org/10.3892/etm.2017.5430
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Abstract

Due to the clinical durable scanning time and other physical constraints, the spatial resolution of diffusion‑weighted magnetic resonance imaging (DWI) is highly limited. Using a post‑processing method to improve the resolution of DWI holds the potential to improve the investigation of smaller white‑matter structures and to reduce partial volume effects. In the present study, a novel non‑local mean super‑resolution method was proposed to increase the spatial resolution of DWI datasets. Based on a non‑local strategy, joint information from the adjacent scanning directions was taken advantage of through the implementation of a novel weighting scheme. Besides this, an efficient rotationally invariant similarity measure was introduced for further improvement of high‑resolution image reconstruction and computational efficiency. Quantitative and qualitative comparisons in synthetic and real DWI datasets demonstrated that the proposed method significantly enhanced the resolution of DWI, and is thus beneficial in improving the estimation accuracy for diffusion tensor imaging as well as high‑angular resolution diffusion imaging.
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Copy and paste a formatted citation
Spandidos Publications style
Yang Z, He P, Zhou J and Wu X: Non‑local diffusion‑weighted image super‑resolution using collaborative joint information. Exp Ther Med 15: 217-225, 2018.
APA
Yang, Z., He, P., Zhou, J., & Wu, X. (2018). Non‑local diffusion‑weighted image super‑resolution using collaborative joint information. Experimental and Therapeutic Medicine, 15, 217-225. https://doi.org/10.3892/etm.2017.5430
MLA
Yang, Z., He, P., Zhou, J., Wu, X."Non‑local diffusion‑weighted image super‑resolution using collaborative joint information". Experimental and Therapeutic Medicine 15.1 (2018): 217-225.
Chicago
Yang, Z., He, P., Zhou, J., Wu, X."Non‑local diffusion‑weighted image super‑resolution using collaborative joint information". Experimental and Therapeutic Medicine 15, no. 1 (2018): 217-225. https://doi.org/10.3892/etm.2017.5430
Copy and paste a formatted citation
x
Spandidos Publications style
Yang Z, He P, Zhou J and Wu X: Non‑local diffusion‑weighted image super‑resolution using collaborative joint information. Exp Ther Med 15: 217-225, 2018.
APA
Yang, Z., He, P., Zhou, J., & Wu, X. (2018). Non‑local diffusion‑weighted image super‑resolution using collaborative joint information. Experimental and Therapeutic Medicine, 15, 217-225. https://doi.org/10.3892/etm.2017.5430
MLA
Yang, Z., He, P., Zhou, J., Wu, X."Non‑local diffusion‑weighted image super‑resolution using collaborative joint information". Experimental and Therapeutic Medicine 15.1 (2018): 217-225.
Chicago
Yang, Z., He, P., Zhou, J., Wu, X."Non‑local diffusion‑weighted image super‑resolution using collaborative joint information". Experimental and Therapeutic Medicine 15, no. 1 (2018): 217-225. https://doi.org/10.3892/etm.2017.5430
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