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Novel methods in biomedical image acquisition and analysis

Resource type
Thesis type
(Thesis) Ph.D.
Date created
2013-05-06
Authors/Contributors
Abstract
Accurate biomedical image acquisition and subsequent analysis are crucial for correctly diagnosing a pathology. This thesis specifically focuses on two different types of biomed- ical imaging techniques - neuro and ophthalmic imaging. The main contribution of this dissertation to neuroimaging is the proposition of a new cortical biomarker, derived from structural Magnetic Resonance Images, and a new analysis methodology that could lead to earlier and better accuracy in distinguishing between healthy subjects and ones suffering from neurodegenerative diseases, such as Alzheimer’s. In the slowly-progressing Alzheimer’s disease, changes in the brain can begin to take place as early as ten years before any clinical symptoms will begin to appear. Early diagnosis of this debilitating diseases can significantly improve the chances of a speedy and successful recovery. In ophthalmic imaging, Optical Coherence Tomography (OCT) is rapidly emerging as the preferred modality in imaging and subsequently diagnosing diseases such as glaucoma and age-related macular degeneration. While OCT is starting to gain popularity among ophthalmologists, it still suffers from a number of draw-backs, including long acquisition times and consequential motion artifacts. The main contribution of this thesis to ophthalmic imaging is to propose several new OCT scan patterns that are compatible with commercial OCT hardware. We show that these scan patterns can significantly reduce the overall scan time, limit motion artifacts, and reduce speckle noise without degrading the quality of the resulting images in terms of clinically relevant morphometric measurements. The acquisition methods presented in this thesis could lead to improved diagnostic power of OCT.
Document
Identifier
etd7853
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Copyright is held by the author.
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The author granted permission for the file to be printed and for the text to be copied and pasted.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Beg, Mirza Faisal
Member of collection
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etd7853_ELebed.pdf 43.93 MB

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