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High Dimensional Clustering and Applications of Learning Methods

Cui:High Dimensional Clustering and App
Autor: Ying Cui
Verfügbarkeit: nur noch 3 lieferbar
Artikelnummer: 723452
ISBN / EAN: 9783838300801

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This book is divided into two parts. The first part §is about non-redundant clustering and feature §selection for high dimensional data. The second §part is on applying learning techniques to lung§tumor image-guided radiotherapy. In the first part, §a new clustering paradigm is investigated for §exploratory data analysis: find all non-redundant §clustering views of the data. Also a feature §selection method is developed based on the popular §transformation approach: principal component §analysis (PCA). In the second part, machine §learning algorithms are designed to aid lung tumor §image-guided radiotherapy (IGRT). Specifically, §intensive studies are preformed for gating and for §directly tracking the tumor. For gating, two §methods are developed: (1) an ensemble of templates §where the representative templates are selected by §Gaussian mixture clustering, and (2) a support §vector machine (SVM) classifier with radial basis §kernels. For the tracking problem, a multiple-§template matching method is explored to capture the §varying tumor appearance throughout the different §phases of the breathing cycle.


Autor Verlag LAP Lambert Academic Publishing
ISBN / EAN 9783838300801 Bindung Taschenbuch

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