Ensemble Empirical Mode Decomposition of functional Images - Couverture souple

Al-Baddai, Saad ; Ludwig, Bernd ; Lang, Elmar

9783330326422: Ensemble Empirical Mode Decomposition of functional Images

Couverture souple

ISBN 10 : 3330326425 ISBN 13 : 9783330326422

Editeur : LAP LAMBERT Academic Publishing, 2017

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2017
Langue: anglais
ISBN 10: 3330326425
ISBN 13: 9783330326422
Reliure: Broch�
Nombre de pages: 92
Coordonn�es du fabricant: non disponible
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Ensemble Empirical Mode Decomposition of functional Images

Saad Al-Baddai

Edit� par LAP LAMBERT Academic Publishing Jun 2017, 2017

ISBN 10 : 3330326425 ISBN 13 : 9783330326422

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book 'EMD of functional images', explores the potential of canonical two-dimensional ensemble empirical mode decomposition (2DEEMD) and Green's function in tension-based bidimensional EMD (GiTBEMD) to extract textures , so-called bidimensional intrinsic mode functions (BIMFs), of functional biomedical images, especially functional magnetic resonance images (fMRI) taken during a visual task. To identify most informative textures, i.e. BIMFs,a support vector machine (SVM) as well as a random forest (RF) classifiers are employed. Classification performance is used to estimate the discriminative power of extracted BIMFs. The latter are then analyzed according to their spatial distribution of brain activations related with visual task and compared with a canonical general linear model (GLM) analysis employing statistical parametric mapping (SPM). Also, a comparative study, in terms of computational costs and quality of extracted intrinsic modes, between 2DEEMD and GiTBEMD have been done based on the same collected data. 92 pp. Englisch. N� de r�f. du vendeur 9783330326422

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Ensemble Empirical Mode Decomposition of functional Images

Saad Al-Baddai|Bernd Ludwig|Elmar Lang

Edit� par LAP LAMBERT Academic Publishing, 2017

ISBN 10 : 3330326425 ISBN 13 : 9783330326422

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Ensemble Empirical Mode Decomposition of functional Images

Saad Al-Baddai

Edit� par LAP LAMBERT Academic Publishing Jun 2017, 2017

ISBN 10 : 3330326425 ISBN 13 : 9783330326422

Neuf Taschenbuch

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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book 'EMD of functional images', explores the potential of canonical two-dimensional ensemble empirical mode decomposition (2DEEMD) and Green's function in tension-based bidimensional EMD (GiTBEMD) to extract textures , so-called bidimensional intrinsic mode functions (BIMFs), of functional biomedical images, especially functional magnetic resonance images (fMRI) taken during a visual task. To identify most informative textures, i.e. BIMFs,a support vector machine (SVM) as well as a random forest (RF) classifiers are employed. Classification performance is used to estimate the discriminative power of extracted BIMFs. The latter are then analyzed according to their spatial distribution of brain activations related with visual task and compared with a canonical general linear model (GLM) analysis employing statistical parametric mapping (SPM). Also, a comparative study, in terms of computational costs and quality of extracted intrinsic modes, between 2DEEMD and GiTBEMD have been done based on the same collected data.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 92 pp. Englisch. N� de r�f. du vendeur 9783330326422

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Ensemble Empirical Mode Decomposition of functional Images

Saad Al-Baddai

Edit� par LAP LAMBERT Academic Publishing, 2017

ISBN 10 : 3330326425 ISBN 13 : 9783330326422

Neuf Taschenbuch

impression � la demande

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book 'EMD of functional images', explores the potential of canonical two-dimensional ensemble empirical mode decomposition (2DEEMD) and Green's function in tension-based bidimensional EMD (GiTBEMD) to extract textures , so-called bidimensional intrinsic mode functions (BIMFs), of functional biomedical images, especially functional magnetic resonance images (fMRI) taken during a visual task. To identify most informative textures, i.e. BIMFs,a support vector machine (SVM) as well as a random forest (RF) classifiers are employed. Classification performance is used to estimate the discriminative power of extracted BIMFs. The latter are then analyzed according to their spatial distribution of brain activations related with visual task and compared with a canonical general linear model (GLM) analysis employing statistical parametric mapping (SPM). Also, a comparative study, in terms of computational costs and quality of extracted intrinsic modes, between 2DEEMD and GiTBEMD have been done based on the same collected data. N� de r�f. du vendeur 9783330326422

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