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Characterization of Breast Tissues using Texture Analysis: Normal Breast Tissues and Hamartoma - Softcover
Synopsis
The identification of normal breast tissues in mammograms is an important step in identifying abnormal tissues, or masses. The major focus of this study is to use image-processing techniques to characterize the normal breast tissues. Clustering techniques have been developed to classify the breast tissue into one of 5 different tissue types including fat, glandular, connective, dense tissues and pectoral muscle. The classification was achieved by using a novel technique (dSGLD) involving a subset of the elements (the values on the diagonals) in the Spatial Grey Level Dependence (SGLD) matrix which was calculated using texture features. The ultimate goal of this study is therefore to design and implement a computerized characterization method that mimics the radiologist’s characterization of tissue composition in digitized mammograms. The classification results using dSGLD and SGLD features achieved an acceptable accuracy.
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About the Author
The Author born in 1965-Sudan, joined the University studies at Sudan University of Science and Technology, College of Medical Radiologic Sience and graduated in 1998 with B. Sc. degree in Radiation Therapy, and awarded M.Sc. in Radiation Therapy in 2000 SUST and Awarded Ph.D. in Medical Physics 2007-Natal University-South Africa.
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Characterization of Breast Tissues using Texture Analysis
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LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3845435666
ISBN 13: 9783845435664
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The identification of normal breast tissues in mammograms is an important step in identifying abnormal tissues, or masses. The major focus of this study is to use image-processing techniques to characterize the normal breast tissues. Clustering techniques have been developed to classify the breast tissue into one of 5 different tissue types including fat, glandular, connective, dense tissues and pectoral muscle. The classification was achieved by using a novel technique (dSGLD) involving a subset of the elements (the values on the diagonals) in the Spatial Grey Level Dependence (SGLD) matrix which was calculated using texture features. The ultimate goal of this study is therefore to design and implement a computerized characterization method that mimics the radiologist s characterization of tissue composition in digitized mammograms. The classification results using dSGLD and SGLD features achieved an acceptable accuracy. 180 pp. Englisch. Seller Inventory # 9783845435664
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Characterization of Breast Tissues using Texture Analysis
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ISBN 10: 3845435666
ISBN 13: 9783845435664
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gar-elnabi MohamedThe Author born in 1965-Sudan, joined the University studies at Sudan University of Science and Technology, College of Medical Radiologic Sience and graduated in 1998 with B. Sc. degree in Radiation Therapy, and awa. Seller Inventory # 5482445
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Characterization of Breast Tissues using Texture Analysis : Normal Breast Tissues and Hamartoma
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845435666
ISBN 13: 9783845435664
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The identification of normal breast tissues in mammograms is an important step in identifying abnormal tissues, or masses. The major focus of this study is to use image-processing techniques to characterize the normal breast tissues. Clustering techniques have been developed to classify the breast tissue into one of 5 different tissue types including fat, glandular, connective, dense tissues and pectoral muscle. The classification was achieved by using a novel technique (dSGLD) involving a subset of the elements (the values on the diagonals) in the Spatial Grey Level Dependence (SGLD) matrix which was calculated using texture features. The ultimate goal of this study is therefore to design and implement a computerized characterization method that mimics the radiologist s characterization of tissue composition in digitized mammograms. The classification results using dSGLD and SGLD features achieved an acceptable accuracy. Seller Inventory # 9783845435664
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Characterization of Breast Tissues using Texture Analysis | Normal Breast Tissues and Hamartoma
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ISBN 10: 3845435666
ISBN 13: 9783845435664
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Taschenbuch. Condition: Neu. Characterization of Breast Tissues using Texture Analysis | Normal Breast Tissues and Hamartoma | Mohamed Gar-Elnabi (u. a.) | Taschenbuch | 180 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845435664 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106778030
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Characterization of Breast Tissues using Texture Analysis
Published by
LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10: 3845435666
ISBN 13: 9783845435664
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The identification of normal breast tissues in mammograms is an important step in identifying abnormal tissues, or masses. The major focus of this study is to use image-processing techniques to characterize the normal breast tissues. Clustering techniques have been developed to classify the breast tissue into one of 5 different tissue types including fat, glandular, connective, dense tissues and pectoral muscle. The classification was achieved by using a novel technique (dSGLD) involving a subset of the elements (the values on the diagonals) in the Spatial Grey Level Dependence (SGLD) matrix which was calculated using texture features. The ultimate goal of this study is therefore to design and implement a computerized characterization method that mimics the radiologist¿s characterization of tissue composition in digitized mammograms. The classification results using dSGLD and SGLD features achieved an acceptable accuracy.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch. Seller Inventory # 9783845435664
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Characterization of Breast Tissues using Texture Analysis: Normal Breast Tissues and Hamartoma
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