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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Condizione: New. pp. 290.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2014
ISBN 10: 1493905996 ISBN 13: 9781493905997
Da: Revaluation Books, Exeter, Regno Unito
EUR 80,56
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Aggiungi al carrelloHardcover. Condizione: Brand New. 285 pages. 9.50x6.50x1.00 inches. In Stock.
Lingua: Inglese
Editore: Springer New York, Springer US, 2014
ISBN 10: 1493905996 ISBN 13: 9781493905997
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,55
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness.
Lingua: Inglese
Editore: Springer New York Apr 2014, 2014
ISBN 10: 1493905996 ISBN 13: 9781493905997
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,49
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness. 288 pp. Englisch.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Da: Majestic Books, Hounslow, Regno Unito
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 290 122 Illus. (58 Col.).
Da: Biblios, Frankfurt am main, HESSE, Germania
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 290.
Da: moluna, Greven, Germania
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an award winning image analysis technology (Thomas Edison Patent Award, MICCAI Young Investigator Award) that achieves object detection and segmentation with state-of-the-art accuracy and efficiencyFlexible, machine learning-based framewo.
Lingua: Inglese
Editore: Springer, Springer Apr 2014, 2014
ISBN 10: 1493905996 ISBN 13: 9781493905997
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 53,49
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications. This book presents an efficient object detection and segmentation framework, called Marginal Space Learning, which runs at a sub-second speed on a current desktop computer, faster than the state-of-the-art. Trained with a sufficient number of data sets, Marginal Space Learning is also robust under imaging artifacts, noise and anatomical variations. The book showcases 35 clinical applications of Marginal Space Learning and its extensions to detecting and segmenting various anatomical structures, such as the heart, liver, lymph nodes and prostate in major medical imaging modalities (CT, MRI, X-Ray and Ultrasound), demonstrating its efficiency and robustness.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 288 pp. Englisch.