Designing Multi-Scale Algorithms for Medical Image Analysis Posted By: David Kennedy - Aug 6, 2008Tool/Resource: Conferences, Workshops and Meetings MICCAI 2008 Tutorial: Designing Multi-Scale Algorithms for Medical Image Analysis Objectives: The teaching of efficient and mathematically well funded multi-scale image analysis techniques for the design of advanced algorithms to the MICCAI community. Justification: Modern image analysis needs substantial understanding of the mathematical underpinning of the applied algorithms. This course invites to 'play with the math' by introducing the multi-scale framework. Emphasis: We show that we can learn a lot from models of human visual perception. Some examples we will touch: - the retina can actually be seen as a multi-resolution camera, sending a scale-space stack to the brain; - the retina consists of two types of ganglion cells, so is effectively two multi-resolution cameras, one for shape and one for motion; - cortical 'simple cells' can be modelled as Gaussian derivatives, taking high order multi-scale derivatives at each pixel; - feedback from cortex to the thalamus can be modelled as adaptive diffusion, for many forms of geometry-driven, edge preserving smoothing; - brain plasticity (self-organization) can be mimicked by eigen-analysis of small image patches, leading to optimal kernels for each image type; - modern optical techniques by voltage sensitive dyes have revealed an intricate structure for multi-orientation analysis (http://www.weizmann.ac.il/brain/grinvald...); this invites to generalize the notion of convolution (normal convolution: translation of the kernel; wavelet convolution: dilation of the kernel; multi-scale convolution: blurring of the kernel; oriented convolution: rotation of the kernel), all leading to very rich high dimensional 'deep' data structures, which the visual system seems to exploit simultaneously. So does the 'multi-orientation score' contain tensor voting, and opens nice and natural possibilities for HARDI analysis. We use Mathematica 6, that has now unequalled possibilities for mathematical interactivity and speed. It integrates symbolics, fast numerics (now faster than Matlab) and excellent graphics. This revolution should not go unnoticed to the MICCAI community. Tutorial speaker: Prof. Bart M. ter Haar Romeny (Eindhoven University of Technology) Date and time: Wednesday morning 10 September 2008, 08:00 am - 12:00 noon. See full description at: http://bmia.bmt.tue.nl/people/BRomeny/MI... |
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