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Segmentation of hand bone for bone age assessment / Yan Chai Hum.

LIBRA RC930 .H86 2013
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Format:
Book
Author/Creator:
Hum, Yan Chai, author.
Series:
SpringerBriefs in applied sciences and technology 2191-530X
SpringerBriefs in applied sciences and technology, 2191-530X
Language:
English
Subjects (All):
Bones--Radiography.
Bones.
Bones--Growth.
Skeletal maturity.
Radiography.
Hand Bones--diagnostic imaging.
Age Determination by Skeleton--methods.
Image Enhancement--methods.
Image Interpretation, Computer-Assisted--methods.
Pattern Recognition, Automated--methods.
Osteogenesis.
Age Determination by Skeleton.
Medical Subjects:
Hand Bones--diagnostic imaging.
Radiography.
Age Determination by Skeleton--methods.
Image Enhancement--methods.
Image Interpretation, Computer-Assisted--methods.
Pattern Recognition, Automated--methods.
Osteogenesis.
Age Determination by Skeleton.
Physical Description:
xvi 132 pages : illustrations ; 24 cm.
Place of Publication:
Singapore : Springer, [2013]
Summary:
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.
Contents:
Introduction
Literature Reviews
Design and Implementation
Result and Discussion
Conclusion and Future Works.
Notes:
Includes bibliographical references and index.
ISBN:
9789814451659
9814451657
OCLC:
834444128

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