Date of Award

1-1-2014

Thesis Type

masters

Document Type

Thesis

Divisions

eng

Department

Faculty of Engineering

Institution

University of Malaya

Abstract

Knee Osteoarthritis (OA) is one of the most common diseases among the elderly. Typically, medical attention is not sought until the disease has progressed to a point at which it is not possible to diagnose effectively, often due to concerns over the cost of detection at an earlier stage. Ultrasound (US) imaging has a number of advantages as an imaging technique; it is a low cost diagnostic method, non-invasive, non-ionizing and able to provide intuitive visualization. There is a significant change in the shape of cartilage due to the progression of knee OA and its associated cartilage degeneration. By using US imaging, it is possible to detect knee joint space narrowing. Nevertheless, the low contrast ratio and presence of speckle noise limit this application of US. The objective of this thesis is to propose a new contrast enhancing and speckle reducing method which will overcome the existing limitations. In the proposed method, contrast enhancement for optimum values of contrast, brightness and detail preservation will be taken into consideration. Most of the conventional contrast enhancing methods emphasize only one character; in contrast, the proposed method involves establishing a separating point to segment histogram for optimal contrast, brightness and detail preservation simultaneously. Three metrics will be used in this optimization, namely Preservation of Brightness Score function (PBS), Optimum Contrast Score function (OCS), and Preservation of Detail Score function (PDS), each of which will be defined. To both reduce speckle noise and preserve edge features, a new diffusivity function and four gradient thresholds instead of one are used. For performance analysis, quantitative and qualitative analysis has been performed using both synthetic and real ultrasound images. Results prove that the proposed method out-performs existing methods.

Note

Thesis (M.Eng.) - Faculty of Engineering, University of Malaya, 2014.

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