Date of Award

5-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Bioengineering

Advisor

Dean, Delphine

Committee Member

Dean , Brian

Committee Member

Kwartowitz , David

Abstract

In this master's thesis, several digital image processing techniques are explored for potential in evaluation of Brightness mode (B-mode) ultrasound images. Currently, many processing techniques are utilized during ultrasound visualization in cardiovascular applications, mammography, and three-dimensional ultrasound systems. However, approaches that serve to aid the clinician in diagnostic assessment of tendinous and ligamentous injuries are more limited. Consequently, the methods employed below are aimed at reducing the dependence on clinician judgment alone to assess the healing stage and mechanical properties of tendinous injuries. Initial focus concentrated on the use of entropy in texture analysis to relate a tendon's appearance in an ultrasound image to its mechanical integrity. Confounding effects such as motion artifacts and region of interest selection by the user limited the applicability of small regions selected for analysis, but general trends were observed when the entire visualized tendon or superficial background region was selected. Entropy calculations suggested a significant change in texture pattern for tendinous regions compared to the selected background regions. In order to reduce the impact of motion artifacts and dependence of the texture analysis on manual identification of regions of interest, a Matlab® script was developed intended to isolate the tendinous regions of interest for further analysis. Methods for segmentation employed relied on a moving window Fourier Transform to compare local parameters in the image to a predefined window of tendinous tissue. Further assessment of each local region benefited from parameterization of the local window's properties that focused on capturing indicators of mean pixel intensity, local variation in pixel intensity, and local directionality consistency derived from the spatial frequency patterns observed in the Fourier Transforms via comparison by the circular Earth Mover's Distance. Results of the segmentation algorithm developed indicated the presence of directional consistency within the tendinous regions, and changes in the speckle pattern were observed for the image derived from mean intensity and local pixel intensity variation. However, non-tendinous regions were also identified for their directional consistency, limiting the applicability of the current process in tendinous region isolation. The results obtained for calculations of the circular Earth Mover's Distance improved slightly with the inclusion of temporal averaging and image registration, but still require improvement before implementation in clinical applications can be realized.

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