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Course description

This course will cover the fundamental components of medical image analysis and visualisation. It will start with an introduction to the underlying concepts and mathematics of biomedical image processing including data storage types and co-ordinate systems. This will be followed by the low level image processing techniques of Quality Control, Intensity Correction, Registration and Segmentation.

The remainder of the course will focus on specific examples of high-level image processing and their application in medical imaging. The examples covered may include Non-linear registration, minimum deformation atlas creation, image fusion or cross modality data, gradient distortion correction, model based segmentation, image analysis in the Diffusion MRI, Perfusion bolus map calculation and an introduction to the General Linear Model (GLM). In addition to this theoretical background, students will be expected to work through real data examples using common image analysis tools.

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