Muhammad Shoaib Ali, Md Belayet Hossain, Yan Chai Hum, Joon Huang Chuah, Maheza Irna Mohd Salim and Khin Wee Lai * Pages 1 - 12 ( 12 )
Background: Ultrasound (US) imaging can be a convenient and reliable substitute for magnetic resonance imaging in the investigation or screening of articular cartilage injury. However, US images suffer from two main impediments, i.e., low contrast ratio and presence of speckle noise.
Aims: A variation of anisotropic diffusion is proposed that can reduce speckle noise without compromising the image quality of the edges and other important details.
Methods: For this technique, four gradient thresholds were adopted instead of one. A new diffusivity function that preserves the edge of the resultant image is also proposed. To automatically terminate the iterative procedures, the Mean Absolute Error as its stopping criterion was implemented.
Results: Numerical results obtained by simulations unanimously indicate that the proposed method outperforms conventional speckle reduction techniques. Nevertheless, this preliminary study has been conducted based on a small number of asymptomatic subjects.
Conclusion: Future work must investigate the feasibility of this method in a large cohort and its clinical validity through testing subjects with a symptomatic cartilage injury.
Ultrasound, Osteoarthritis, anisotropic diffusion, diffusivity function, gradients, flow function, edge preservation, speckle noisUltrasound, speckle noise
Department of Biomedical Engineering, Faculty of Engineering, University Malaya, 50603 Kuala Lumpur, School of Info Technology, Faculty of Sci Eng & Built Env, Deakin University, Melbourne, Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Bandar Sungai Long, Cheras, 43000 Kajang, Selangor Darul Ehsan, VIP Research Lab, Department of Electrical Engineering, Faculty of Engineering, University Malaya, 50603 Kuala Lumpur, Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Department of Biomedical Engineering, Faculty of Engineering, University Malaya, 50603 Kuala Lumpur