Speckle-noise reduction in knee articular cartilage ultrasound image using anisotropic diffusion / Muhammad Shoaib Ali
Knee arthritis is the most common type of arthritis which effects the people and may cause severe pain to the patient and can lead to joint effusion. Ultrasound (US) imaging is an appropriate and consistent substitute for other imaging techniques like magnetic resonance imaging or X-rays in the inve...
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| Format: | Thesis |
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2020
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| Online Access: | http://studentsrepo.um.edu.my/11904/ http://studentsrepo.um.edu.my/11904/1/Muhammad_Shoaib_Ali.jpg http://studentsrepo.um.edu.my/11904/8/shoaib.pdf |
| Summary: | Knee arthritis is the most common type of arthritis which effects the people and may cause severe pain to the patient and can lead to joint effusion. Ultrasound (US) imaging is an appropriate and consistent substitute for other imaging techniques like magnetic resonance imaging or X-rays in the investigation or screening of knee injury. Nevertheless, one of the major problems in US images which make the analysis of these images hard is the presence of speckle noise. For the reduction of speckle noise, the performance of the anisotropic method is found much better over other approaches. In removing the speckle noise, mostly used methods diffuse the edges during the diffusion of the homogenous region of US images. Therefore, the very critical task is to preserve the edges during the diffusion process. In this research, a method based on Anisotropic Diffusion (AD) is proposed to reduce the speckle noise. The proposed variation in the AD method not only reduces the speckle noise but also preserves the edges and other important detail of images efficiently. Four gradient thresholds are proposed instead of one to have comprehensive information of all neighbouring pixels. A new diffusivity function is also proposed to preserve the edges by stopping diffusion abruptly nears edges. Four different evaluation metrics i.e. Peak Signal-to-Noise Ratio (PSNR), Structure Similarity Index Measurement (SSIM), Figure of Merit (FOM), and Equivalent Number of Looks (ENL) are used to evaluate the performance of the proposed method. Numerical results attained by simulations show that the proposed method reduces the speckle noise very effectively and preserves the edges as well. |
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