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Subtle changes in brain tissue that reflect the pathological processes of disorders such as mild cognitive impairment (MCI) are much more difficult to observe on a patient's magnetic resonance imaging (MRI) scan than those obvious abnormalities such as large strokes or tumors. Thus, it is necessary to develop an automated computer-aided diagnosis (CAD) system which will be more efficient and accurate...
Multimodality MR image processing and analysis aims to determine to what extent information from various imaging modalities is redundant or complementary and how changes in various regions of the brain, detected by various modalities, interact with each other to produce cognitive and functional changes. Here, we presented a multimodality image processing framework to integrate unique and complementary...
Liver segmentation on computed tomography (CT) images is a challenging task due to the anatomic complexity and the imaging system noise. In this paper, we develop an improved level set segmentation method. Our region-based level-set approach has many advantages over the conventional active contour models. First, the improved model can get much smoother contour by adding a signed distance preserving...
Magnetic resonance imaging (MRI) is used to visualize the anatomy and structure of a body organ for assistance in medical diagnostics of certain disease or conditions and to evaluate a particular disease. Magnetic resonance images of a specified anatomy are constructed by using radio waves, a magnetic field and compute. This technical paper demonstrates the segmentation process of brain MR images...
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