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Segmentation Hand Bone Age by Hum Yan (12 results)
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Segmentation of Hand Bone for Bone Age Assessment (SpringerBriefs in Applied Sciences and Technology)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 48.98
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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PF. Condition: New.
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Condition: New. pp. 150.
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Paperback. Condition: Brand New. 2013 edition. 148 pages. 9.25x6.10x0.35 inches. In Stock.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. The task is accomplished by first applying the modified histogram equalized module, then applying the proposed automated anisotropic diffusion technique. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme. The designed segmentation framework works without demanding scarce resources such as training sets and skillful operators. The results have shown that the designed framework is capable of separating the soft-tissue and background from the hand bone with high accuracy. This Brief should be especially useful for students and professional researchers in the Biomedical and image processing fields.
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Taschenbuch. Condition: Neu. Segmentation of Hand Bone for Bone Age Assessment | Yan Chai Hum | Taschenbuch | SpringerBriefs in Applied Sciences and Technology | xvi | Englisch | 2013 | Springer | EAN 9789814451659 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Paperback. Condition: Like New. Like New. book.
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Segmentation of Hand Bone for Bone Age Assessment
Language: English
Published by Springer Nature Singapore Jun 2013, 2013
ISBN 10: 9814451657 ISBN 13: 9789814451659
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. The task is accomplished by first applying the modified histogram equalized module, then applying the proposed automated anisotropic diffusion technique. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme. The designed segmentation framework works without demanding scarce resources such as training sets and skillful operators. The results have shown that the designed framework is capable of separating the soft-tissue and background from the hand bone with high accuracy. This Brief should be especially useful for students and professional researchers in the Biomedical and image processing fields. 148 pp. Englisch.
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Condition: New. Print on Demand pp. 150.
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Condition: New. PRINT ON DEMAND pp. 150.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Hum Yan Chai received his PhD in the field of Biomedical Imaging from the Universiti Teknologi Malaysia (UTM). He is currently working as a researcher in the Medical Implant Technology Group (MEDITEG), Materials and Manufacturing Research Alliance. His .
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Segmentation of Hand Bone for Bone Age Assessment
Language: English
Published by Springer, Springer Jun 2013, 2013
ISBN 10: 9814451657 ISBN 13: 9789814451659
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. The task is accomplished by first applying the modified histogram equalized module, then applying the proposed automated anisotropic diffusion technique. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme. The designed segmentation framework works without demanding scarce resources such as training sets and skillful operators. The results have shown that the designed framework is capable of separating the soft-tissue and background from the hand bone with high accuracy. This Brief should be especially useful for students and professional researchers in the Biomedical and image processing fields.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.
