Haegler katrin (15 resultados)

Autor
Refinar con la Búsqueda avanzada

Filtrar la búsqueda

  • Libros (15)

a

Intervalo de precios personalizado (EUR)

a

  • Idioma: Inglés

    Editorial: S?dwestdeutscher Verlag f?r Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 61,46

     Gastos de envío gratis 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 1 disponibles

    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: S?dwestdeutscher Verlag f?r Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 59,70

    Envío por EUR 4,85 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 63,92

    Envío por EUR 2,30 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Usado - Como Nuevo

    EUR 73,13

    Envío por EUR 2,30 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 63,59

    Envío por EUR 17,49 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag für Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Usado - Como Nuevo

    EUR 76,17

    Envío por EUR 17,49 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag Für Hochschulschriften, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 93,61

    Envío por EUR 11,66 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    Paperback. Condición: Brand New. 164 pages. 8.66x5.91x0.37 inches. In Stock.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: Wegmann1855, Zwiesel, AlemaniaWegmann1855

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 79,90

    Envío por EUR 25,95 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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, 2015

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: preigu, Osnabrück, Alemaniapreigu

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 65,20

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 113,15

    Envío por EUR 30,50 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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

    3838131711 / 9783838131719

    • Tapa blanda

    Librería: Books-by-Floh, Paderborn, AlemaniaBooks-by-Floh

    Vendedor de 4 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 106,73

    Envío por EUR 105,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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.

  • Idioma: Inglés

    Editorial: Südwestdeutscher Verlag Für Hochschulschriften Mär 2012, 2012

    3838131711 / 9783838131719

    • Tapa blanda
    • Impresión bajo demanda

    Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 79,90

    Envío por EUR 23,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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

    3838131711 / 9783838131719

    • Tapa blanda
    • Impresión bajo demanda

    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 79,90

    Envío por EUR 23,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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

    3838131711 / 9783838131719

    • Tapa blanda
    • Impresión bajo demanda

    Librería: moluna, Greven, Alemaniamoluna

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 64,09

    Envío por EUR 48,99 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    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

    3838131711 / 9783838131719

    • Tapa blanda
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 79,90

    Envío por EUR 60,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponibles

    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.