Similarity Search in Medical Data : Automatic differentiation between low- and high-grade brain tumors

Language: English

Published by Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012

3838131711 / 9783838131719

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Neuware - At present, an adequate therapy planning of newly detected brain tumors needs invasive biopsy due to the fact that prognosis and treatment, both vary strongly for different tumor grades. To assist neuroradiologist experts during the differentiation between tumors of different malignancy a novel, efficient similarity search technique for uncertain data in combination with a technique for parameter-free outlier detection is proposed. Previous work is limited to axis-parallel Gaussian distributions, hence, correlations between different features are not considered in these similarity searches. In this work a similarity search technique for general Gaussian Mixture Models (GMMs) without independence assumption is presented. The actual components of a GMM are approximated in a conservative but tight way. The conservativity of the approach leads to a filter-refinement architecture, which guarantees no false dismissals and the tightness of the approximations causes good filter selectivity. Promising results for advancing the differentiation between brain tumors of different grades could be obtained by applying the approach to four-dimensional Magnetic Resonance Images of glioma patients.

Seller Inventory # 9783838131719

Title
Similarity Search in Medical Data : Automatic differentiation between low- and high-grade brain tumors
Author
Katrin Haegler
Publisher
Südwestdeutscher Verlag Für Hochschulschriften Mär 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3838131711
ISBN 13
9783838131719
Item weight
262 grams
Dimensions
220x150x11 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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