Titlebook: Handbook of Biomedical Imaging; Methodologies and Cl Nikos Paragios,James Duncan,Nicholas Ayache Book 2015 Springer Science+Business Media

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Fuzzy methods in medical imaginghematical framework for knowledge representation, information modeling at different levels, fusion of heterogeneous information, reasoning and decision making. In this chapter, we provide an overview of the potential of this theory in medical imaging, in particular for classification, segmentation a

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Curve Propagation, Level Set Methods and Groupingtutorial of level sets towards a flexible frame partition paradigm that could integrate edge-drive, regional-based and prior knowledge to object extraction. The central idea behind such an approach is to perform image partition through the propagation planar curves/surfaces. To this end, an objectiv

闡明

Kernel Methods in Medical Imagingtation of machine learning concepts and tools, including Support Vector Machine (SVM), kernel ridge regression and kernel PCA, we present an application of these tools to the prediction of Computed Tomography (CT) images based on Magnetic Resonance (MR) images.

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