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    ANALYSIS OF ANATOMICAL BRANCHING STRUCTURES

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    TETDEDXNuzhnaya-temple-0225E-1 ...
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    Genre
    Thesis/Dissertation
    Date
    2015
    Author
    Nuzhnaya, Tatyana
    Advisor
    Megalooikonomou, Vasilis
    Ling, Haibin
    Committee member
    Megalooikonomou, Vasilis
    Ling, Haibin
    Lakaemper, Rolf
    Yang, Jie
    Department
    Computer and Information Science
    Subject
    Computer Science
    Artificial Intelligence
    Medical Imaging and Radiology
    Detection
    Medical Imaging
    Segmentation
    Texture Features
    Topological Descriptors
    Tree-like Structures
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/3347
    
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    DOI
    http://dx.doi.org/10.34944/dspace/3329
    Abstract
    Development of state-of-the-art medical imaging modalities such as Magnetic Resonance Imaging, Computed Tomography, Galactography, MR Diffusion Tensor Imaging, and Tomosynthesis plays an important role for visualization and assessment of anatomical structures. Included among these structures are structures of branching topology such as the bronchial tree in chest computed tomography images, the blood vessels in retinal images and the breast ductal network in x-ray galactograms and the tubular bone patterns in dental radiography. Analysis of such images could help reveal abnormalities, assist in estimating a risk of diseases such as breast cancer and COPD, and aid in the development of realistic anatomy phantoms. This thesis aims at the development of a set of automated methods for the analysis of anatomical structures of tree and network topology. More specifically, the two main objectives include (i) the development of analysis framework to explore the association between topology and texture patterns of anatomical branching structures and (ii) the development of the image processing methods for enhanced visualization of regions of interest in anatomical branching structures such as branching nodes.
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