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Segmentation of Hand Bone for Bone Age Assessment [electronic resource] / by Yan Chai Hum.

By: Hum, Yan Chai [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Applied Sciences and Technology: Publisher: Singapore : Springer Singapore : Imprint: Springer, 2013Description: XVI, 132 p. 51 illus., 27 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789814451666.Subject(s): Engineering | Radiology | Medical physics | Radiation | Biomedical engineering | Engineering | Biomedical Engineering | Signal, Image and Speech Processing | Imaging / Radiology | Medical and Radiation PhysicsAdditional physical formats: Printed edition:: No titleDDC classification: 610.28 Online resources: Click here to access online
Contents:
Introduction -- The conventional segmentation methods -- The advanced segmentation method -- The possible solution -- Result analysis and discussion -- Conclusions and recommendations.
In: Springer eBooksSummary: 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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Introduction -- The conventional segmentation methods -- The advanced segmentation method -- The possible solution -- Result analysis and discussion -- Conclusions and recommendations.

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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