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Flux-based Curvilinear Structure Analysis
PhD Thesis Proposal Defence Title: "Flux-based Curvilinear Structure Analysis" by Mr. Jierong WANG Abstract: The curvilinear structure is a vital clue in many vessel diseases. During curvilinear structure analysis, high-level information such as eccentricity, scale, structural orientation, and abnormality can be collected for disease diagnosis and pathology quantification. Among a wide range of techniques for curvilinear structure analysis, linear descriptors based on various assumptions and prior knowledge of the target structures have been drawing attention for decades. In the first proposed method, we extend the flux descriptor using an oriented cylindrical model whose centerline is curvilinear and the model orientation is homogeneous with the object orientation. Then, higher-order tensor construction and decomposition framework is adopted to further improve orientation coherence. Our second method is an efficient manipulation of the higher-order tensor combined with the oriented flux. We construct the higher-order tensor in the frequency domain with the help of spherical harmonics transform and calculate fiber orientation distribution function for vascular responses. In our third work, we improve the optimally oriented flux in two aspects: normal plane (eccentricity), and orientation. While the first three proposed methods concentrate on the improvement of the low-level descriptors, the last presented method contribute to the graphical framework. Concretely, in our fourth work, the random walks framework is improved by a modified Forman's curvature function, which is modeled in sub-pixel resolution and can capture details in a higher order. Date: Tuesday, 3 May 2022 Time: 4:00pm - 6:00pm Zoom Meeting: https://hkust.zoom.us/j/93717337886?pwd=L25DS3ZiNUc3ZUZlSUllRzdSUVhYZz09 Committee Members: Prof. Albert Chung (Supervisor) Prof. Chi-Keung Tang (Supervisor) Dr. Xiaojuan Ma (Chairperson) Prof. Pedro Sander **** ALL are Welcome ****