Novel Image Texture Analysis for Advanced Structure Characterization

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Novel Image Texture Analysis for Advanced Structure CharacterizationMy research seeks to develop, extend and validate novel signal processing and analysis algorithms for advanced structure characterization. Currently I am developing new techniques to improve the evaluation of tissue properties from magnetic resonance imaging (MRI) of biological subjects. However, my approaches have broader applications in diverse fields including geoscience, physics, and engineering.The Fourier transform forms the cornerstone of many imaging modalities including MRI and computer tomography (CT). The MR data are initially acquired in the frequency domain and are then reconstructed using the inverse Fourier transform. Therefore, MR images can be processed using advanced, Fourier-based analysis methods to enhance identification of tissue structure without loss of information.Over the past few years I have been engaged in developing and evaluation of advanced methods to detect subtle alterations in the local pattern of image intensity, namely, MR 'texture'. Texture patterns are generally too subtle to be perceived even by trained observers, thus mathematical algorithms are required. My pilot data demonstrate texture analysis to be a sensitive measure of tissue injury and repair.In this proposal, I aim to develop new avenues of texture analysis to enhance health outcomes of Canadians. In particular, I propose to investigate texture spectral imaging and texture anisotropy to improve the sensitivity and specificity of texture analysis. Output from this project may advance our capacity to evaluate tissue structure without modifying existing imaging protocols.