Biomedical image analysis: statistical and variational methods
Ideal for classroom use and self-study, this book explains the implementation of the most effective modern methods in image analysis, covering segmentation, registration and visualisation, and focusing on the key theories, algorithms and applications that have emerged from recent progress in compute...
Gespeichert in:
Beteilige Person: | |
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Format: | E-Book |
Sprache: | Englisch |
Veröffentlicht: |
Cambridge
Cambridge University Press
2014
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Links: | https://doi.org/10.1017/CBO9781139022675 |
Zusammenfassung: | Ideal for classroom use and self-study, this book explains the implementation of the most effective modern methods in image analysis, covering segmentation, registration and visualisation, and focusing on the key theories, algorithms and applications that have emerged from recent progress in computer vision, imaging and computational biomedical science. Structured around five core building blocks - signals, systems, image formation and modality; stochastic models; computational geometry; level set methods; and tools and CAD models - it provides a solid overview of the field. Mathematical and statistical topics are presented in a straightforward manner, enabling the reader to gain a deep understanding of the subject without becoming entangled in mathematical complexities. Theory is connected to practical examples in x-ray, ultrasound, nuclear medicine, MRI and CT imaging, removing the abstract nature of the models and assisting reader understanding, whilst computer simulations, online course slides and a solution manual provide a complete instructor package. |
Umfang: | 1 Online-Ressource (xxii, 464 Seiten) |
ISBN: | 9781139022675 |
Internformat
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id | ZDB-20-CTM-CR9781139022675 |
illustrated | Not Illustrated |
indexdate | 2025-03-03T11:58:05Z |
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isbn | 9781139022675 |
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spelling | Farag, Aly A. Biomedical image analysis statistical and variational methods Aly A. Farag, University of Louisville Cambridge Cambridge University Press 2014 1 Online-Ressource (xxii, 464 Seiten) txt c cr Ideal for classroom use and self-study, this book explains the implementation of the most effective modern methods in image analysis, covering segmentation, registration and visualisation, and focusing on the key theories, algorithms and applications that have emerged from recent progress in computer vision, imaging and computational biomedical science. Structured around five core building blocks - signals, systems, image formation and modality; stochastic models; computational geometry; level set methods; and tools and CAD models - it provides a solid overview of the field. Mathematical and statistical topics are presented in a straightforward manner, enabling the reader to gain a deep understanding of the subject without becoming entangled in mathematical complexities. Theory is connected to practical examples in x-ray, ultrasound, nuclear medicine, MRI and CT imaging, removing the abstract nature of the models and assisting reader understanding, whilst computer simulations, online course slides and a solution manual provide a complete instructor package. Erscheint auch als Druck-Ausgabe 9780521196796 |
spellingShingle | Farag, Aly A. Biomedical image analysis statistical and variational methods |
title | Biomedical image analysis statistical and variational methods |
title_auth | Biomedical image analysis statistical and variational methods |
title_exact_search | Biomedical image analysis statistical and variational methods |
title_full | Biomedical image analysis statistical and variational methods Aly A. Farag, University of Louisville |
title_fullStr | Biomedical image analysis statistical and variational methods Aly A. Farag, University of Louisville |
title_full_unstemmed | Biomedical image analysis statistical and variational methods Aly A. Farag, University of Louisville |
title_short | Biomedical image analysis |
title_sort | biomedical image analysis statistical and variational methods |
title_sub | statistical and variational methods |
work_keys_str_mv | AT faragalya biomedicalimageanalysisstatisticalandvariationalmethods |