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Anisotropic Geodesic Filter for Speckle Noise Reduction and Edge Preservation in 2D and 3D Echocardiography
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- Author / Creator
- Nehan Khan
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It is a challenge today for medical practitioners and manufacturers to improve ultrasound image quality as the technology has reached its physical limits. Ultrasound images are a great help for non-invasive diagnostics but suffer from a wide variety of artifacts such as shadowing, limited field of view, and speckle noise. The main focus of this thesis is on the application of a new non-linear image processing technique in cardiac ultrasound imaging and more specifically on various methods to reduce multiplicative speckle noise. Various filtering techniques for speckle noise reduction have been proposed in the past; however, their performances are still limited as a compromise between speckle noise reduction and image features preservation is difficult to reach.
In this thesis, an anisotropic geodesic filtering algorithm is proposed to reduce the multiplicative noise in cardiac ultrasound images. The algorithm is based on a scale-space filtering technique comparable to Gaussian filtering but with the difference that the Gaussian weights are automatically modified using a non-linear geodesic distance calculation between the pixels which is capable of automatically preserving edges. In the thesis, the proposed anisotropic geodesic filter is compared to various existing filters such as Gaussian filter, median filter, and other types of non-linear filters based on gradient-based anisotropic diffusion. We demonstrate that the proposed anisotropic geodesic filter performs best in terms of preserving features and at the same time can provide improvements to the signal-to-noise-ratio of real-time 2D and 3D echo-cardiographs. The proposed algorithm is validated on real-world ultrasound images comparing signal-to-noise-ratio (SNR), root-mean-square-error (RMSE), peak-signal-to-noise-ratio (PSNR), contrast and contrast-to-noise-ratio (CNR).
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- Graduation date
- Fall 2018
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.