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• W103338145 abstract "THE thesis is dedicated to three dimensional shape analysis and the segmentation ofhuman skeletal muscles in the context of myopathies and their treatment. In particular,we study the local and global structural characteristics of muscles. The methodologicalfocus of the thesis is to devise methods for the segmentation of muscles, theconsistent localization of positions in the anatomy and the navigation within the muscledata across patients. Currently diagnosis and follow-up examinations during therapy ofmyopathies are typically performed by means of biopsy. This has several disadvantages:it is an invasive method, covers only a small muscle region, is mainly restricted to diagnosticpurpose and is not suitable for follow-up evaluation. We develop the followingmethods to make the use of non-invasive imaging modalities such as MRI for a virtualbiopsy possible: first, a novel approach to model shape variations that encodes sparsity,exploits geometric redundancy, and accounts for the different degrees of local variationand image support in data. It makes the modeling and localization of muscles possible,that exhibit sparsely distributed salient imaging features, and heterogeneous shapevariability. Second, we extend the shape representation of 3D structures using diffusionwavelets. The proposed method can represent shape variation and exploits continuousinter-dependencies of arbitrary topology in the shape data. We then explore several approachesfor the shape model search, and appearance representation based on boostingtechniques and canonical correlation analysis. Last we present a robust diffusion wavelettechnique that covers the integration of our two shape models approaches to finally getan enhanced sparse wavelet based method. We validate the approaches on two medicalimaging data sets that represent the properties tackled by the approaches: T1 weightedMRI data of full calf muscles and computed tomography data of the left heart ventricle." @default.
• W103338145 created "2016-06-24" @default.
• W103338145 creator A5057489759 @default.
• W103338145 date "2010-05-12" @default.
• W103338145 modified "2023-09-23" @default.
• W103338145 title "3D Knowledge-based Segmentation Using Sparse Hierarchical Models : contribution and Applications in Medical Imaging" @default.
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