Isbn: 9786202520324 - canny operator based drlse algorithm for medical image segmentation: biomedical image processing (5 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2020

    6202520329 / 9786202520324

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    Librería: moluna, Greven, Alemaniamoluna

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    Editorial: LAP LAMBERT Academic Publishing, 2020

    6202520329 / 9786202520324

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Canny Operator Based DRLSE Algorithm for Medical Image Segmentation | Biomedical Image Processing | Dipali Dhake (u. a.) | Taschenbuch | 76 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202520324 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Apr 2020, 2020

    6202520329 / 9786202520324

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

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the regularity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters. 76 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2020

    6202520329 / 9786202520324

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

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    EUR 45,66

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the regularity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Apr 2020, 2020

    6202520329 / 9786202520324

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    EUR 39,90

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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the regularity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…