Novel Image Texture Analysis for Advanced Structure Characterization

用于高级结构表征的新型图像纹理分析我的研究旨在开发、扩展和验证用于高级结构表征的新型信号处理和分析算法。目前，我正在开发新的技术，以改善生物对象的磁共振成像（MRI）的组织属性的评价。然而，我的方法在包括地球科学、物理学和工程学在内的不同领域有着更广泛的应用。傅立叶变换是许多成像模式的基石，包括MRI和计算机断层扫描（CT）。MR数据首先在频域中采集，然后使用逆傅立叶变换进行重建。因此，可以使用先进的，基于傅立叶的分析方法来处理MR图像，以增强组织结构的识别，而不会丢失信息。在过去的几年里，我一直从事开发和评估先进的方法来检测图像强度的局部模式，即MR“纹理”的细微变化。纹理模式通常太微妙，即使是受过训练的观察者也无法感知，因此需要数学算法。我的试点数据表明，纹理分析是一个敏感的措施组织损伤和repair.In这个提案，我的目标是开发新的途径，纹理分析，以提高加拿大人的健康结果。特别是，我建议研究纹理光谱成像和纹理各向异性，以提高纹理分析的灵敏度和特异性。该项目的输出可能会提高我们在不修改现有成像协议的情况下评估组织结构的能力。

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.