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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Background

Magnetic resonance imaging (MRI) is a handy diagnostic tool for orthopedic disorders, particularly spinal and joint diseases.

Methods

The lumbar intervertebral disc is visible in the T1 and T2 weight sequences of the spine MRI, which aids in diagnosing lumbar disc herniation, lumbar spine tuberculosis, lumbar spine tumors, and other conditions. The lumbar intervertebral disc cannot be seen accurately in the Spectral Attenuated Inversion Recovery (SPAIR) due to weaknesses in the fat and frequency offset parameters, which is not conducive to developing the intelligence diagnosis model of medical image.

Results

In order to solve this problem, we propose a composite framework, which is first to use the contrast limited adaptive histogram equalization (CLAHE) method to enhance the SPAIR image contrast of the spine MRI and then use the non-local means method to remove the noise of the image to ensure that the image contrast is uniform without losing details. We employ the Information Entropy (IE), Peak signal-to-noise ratio (PSNR), and feature similarity index measure (FSIM) to quantify image quality after enhancement by the composite framework.

Conclusion

The outcomes of the experiments’ output images and quantitative data indicate that our composite framework is better than others.

© 2024 The Author(s).
© 2024 The Author(s). Published by Bentham Science Publisher. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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A New Method Used to Enhance the SPAIR Image of the Spine MRI
Curr. Med. Imaging 20, e15734056251482 (2024); https://doi.org/10.2174/0115734056251482231107072125
/content/journals/cmir/10.2174/0115734056251482231107072125
/content/journals/cmir/10.2174/0115734056251482231107072125
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  • Article Type:     Research Article
Keyword(s): Diagnostic tool; MRI; Orthopedic disorder; SPAIR image; The contrast limited adaptive histogram equalization; The non-local means method

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