脊柱(分子生物学)
计算机科学
医学
放射科
生物
生物信息学
作者
Huayu Fan,Xiangyang Cao,Mingxiang Wu,Mingyu Zhao,Liyun Liu,Yongwei Song,Xiangdong Zhang,Binqing Zhang
出处
期刊:Current Medical Imaging Reviews
[Bentham Science]
日期:2024-02-16
卷期号:20
标识
DOI:10.2174/0115734056251482231107072125
摘要
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.
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