Ioannis Kapouleas

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Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previously analyzed and reported in the statistical, medical, or machine learning literature. The data sets are characterized by statisucal uncertainty; there is no completely accurate(More)
Axial and sagittal magnetic resonance (MR) sections and contiguous sections of axial positron emission tomographic (PET) images obtained with fludeoxyglucose F-18 were used to evaluate a new method of registering three-dimensional images of the brain. The users specified the interhemispheric fissure plane in three dimensions for both the MR and PET data(More)
A new approach to automating radiologic diagnosis is described and tested in a system that locates multiple sclerosis lesions in magnetic resonance human brain images. This approach uses a step-by-step procedure, where the most obvious features in the images are identified first, and used to calibrate the application of the next step, until the desired(More)
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