Haegler katrin (15 resultados)

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Editorial: S?dwestdeutscher Verlag f?r Hochschulschriften, 2012
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Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012
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Condición: New.

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Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012
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Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012
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Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012
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Editorial: Südwestdeutscher Verlag Für Hochschulschriften, 2012
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 164 pages. 8.66x5.91x0.37 inches. In Stock.

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Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012
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Librería: Wegmann1855, Zwiesel, AlemaniaWegmann1855
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Taschenbuch. Condición: Neu. 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.…

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Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2015
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Librería: preigu, Osnabrück, Alemaniapreigu
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Taschenbuch. Condición: Neu. Similarity Search in Medical Data | Automatic differentiation between low- and high-grade brain tumors | Katrin Haegler | Taschenbuch | 164 S. | Englisch | 2015 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838131719 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 113,15
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Taschenbuch. Condición: Neu. 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.…

Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012
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Librería: Books-by-Floh, Paderborn, AlemaniaBooks-by-Floh
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Taschenbuch. Condición: Neu. 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. 164 pp. Englisch.…

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Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 164 pp. Englisch.…

Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 79,90
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 164 pp. Englisch.…

Idioma: Inglés
Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012
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Librería: moluna, Greven, Alemaniamoluna
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EUR 64,09
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Haegler KatrinKatrin Haegler, Dr.: Studies of Bioinformatics at Ludwig-Maximilians (LMU) University and Technical University Munich. PhD studentship in Computer Sience at the LMU Munich. Core software engineer at SEP AG, Weyarn, Germ.…

Idioma: Inglés
Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 79,90
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch.…