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Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures - Couverture rigide
Synopsis
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.
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Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures
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Springer, 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
Ancien ou d'occasion
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Marginal Space Learning for Medical Image Analysis
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Springer New York, 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
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Gebunden. Etat : 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. N° de réf. du vendeur 4213849
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Marginal Space Learning for Medical Image Analysis
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Springer New York Apr 2014, 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : 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. N° de réf. du vendeur 9781493905997
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Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures
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Marginal Space Learning for Medical Image Analysis
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Springer New York, Springer US Apr 2014, 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 288 pp. Englisch. N° de réf. du vendeur 9781493905997
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Marginal Space Learning for Medical Image Analysis : Efficient Detection and Segmentation of Anatomical Structures
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Springer New York, Springer US, 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : 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. N° de réf. du vendeur 9781493905997
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Marginal Space Learning for Medical Image Analysis : Efficient Detection and Segmentation of Anatomical Structures
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Marginal Space Learning for Medical Image Analysis : Efficient Detection and Segmentation of Anatomical Structures
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Marginal Space Learning for Medical Image Analysis: Efficient Detection and Segmentation of Anatomical Structures
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Springer-Verlag New York Inc., 2014
ISBN 10 : 1493905996
ISBN 13 : 9781493905997
Neuf
Couverture rigide
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Hardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 575. N° de réf. du vendeur C9781493905997
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Marginal Space Learning for Medical Image Analysis
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