الفهرس 
Cover EnglishOnly 14 pages are availabe for public view
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Abstract
Osteoarthritis is one of the most common disease of joints worldwide that describes articular cartilage degeneration and breakdown. Joint injuries, excessive loading, obesity and aging can affect osteoarthritis. Investigating the surface roughness of the articular cartilage is of great importance to assess the irregularity of the surface. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. Moreover, visual assessment of the articular cartilage surface by arthroscope cannot detect the early signs of degeneration. As the average roughness of the articular cartilage surface is an important indicator of the early signs of osteoarthritis, investigation into a method based on laser speckle, speckle for short, to estimate the average roughness of the articular cartilage surface was proposed. Speckle appears whenever a rough surface is illuminated by highly coherent radiation. Therefore, speckle imaging method is based on the phenomenon that, when a laser radiation illuminates a rough surface, it is backscattered randomly in all directions resulting in an illuminated image with bright and dark spots that carry considerable information about the surface deformation. This image, called speckle pattern, results from the random interference of the backscattering (diffuse reflecting) rays, where the bright spots correspond to constructive interference while the dark spots result from destructive interference. It was intended to use speckle imaging as it is a simple, inexpensive, nondestructive, noncontact and safe method. In this work, an experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to collect speckle patterns of bovine articular cartilage specimens prepared for different average roughness values. Digital image processing by means of different texture analysis methods analyzed on the captured speckle patterns were utilized to estimate the average surface roughness of the articular cartilage specimens. Finally, the proposed method could accurately estimate the average roughness of the articular cartilage surface for early signs of degeneration with an accuracy of 0.02 μm.