Statistical Data Mining for Medical Image Data Analysis

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The aim of this project is to develop new statistical data mining models and methods for medical image data analysis. For example, Diffusion Tensor Imaging (DTI) is an advanced magnetic resonance imaging (MRI) method that benefits clinicians in monitoring human brain disease progression, planning neurosurgery and studying brain development. DTI data analysis must account for the diffusion tensor, which has a complicated mathematical structure, the three-dimensional spatial characteristics of the image, and the existence of complicated fibre structures in the brain. The combination of these aspects makes diffusion tensor image analysis one of the most challenging topics in the area of medical image analysis. Another example is mammography data analysis. To identify mammographic feature (e.g. mass, calcifications and architecture distortion) and to analyse the geometry properties of these features among mammography images are essential for breast cancer screening. To achieve the aim of this project, new techniques will be developed building on the rapidly developing theory of Statistical Date Mining, as well as on Statistical Shape Analysis and Computer Vision.