Inhaltsangabe
Brain tumor is one of the major causes for the increase in mortality among the children and adults. In fact, tumor is a mass of tissue that grows-out of control from the normal forces which regulates growth. Therefore, identification of this in advance helps in the recovery of patients through suggestive and corrective treatments. To identify these brain diseases, it is essential to segment the brain tissues which consist of mainly three parts such as Gray Matter (GM), White Matter (WM) and Cerebro spinal fluid (CSF). There are many segmentation techniques available based on parametric and non-parametric models. Among these models, segmentation of medical images based on parametric technique is more accurate. In model based segmentation, entire image is viewed as a collection of image region. Finite mixture models are utilized to characterize the pixel intensities inside the images. Hence, Finite Skew Gaussian Mixture model is used to carry out the segmentation process, the initial parameters are obtaining by using clustering algorithms and the updated equations are obtained by deriving the equations using EM algorithm.
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Über die Autorin bzw. den Autor
Dr. Nagesh Vadaparthi is a Professor in the department of Information Technology, Maharaj Vijayaram Gajapathi Raj College of Engineering, India. He has published various papers in reputed National and International Journals and Conferences. His areas of interest are Medical Image Processing, Grid Computing and Hadoop & Big Data Analytics.
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Segmentation of Medical MR Images Using Skew Gaussian Distribution
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LAP LAMBERT Academic Publishing Jun 2018, 2018
ISBN 10: 6139832829
ISBN 13: 9786139832828
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Brain tumor is one of the major causes for the increase in mortality among the children and adults. In fact, tumor is a mass of tissue that grows-out of control from the normal forces which regulates growth. Therefore, identification of this in advance helps in the recovery of patients through suggestive and corrective treatments. To identify these brain diseases, it is essential to segment the brain tissues which consist of mainly three parts such as Gray Matter (GM), White Matter (WM) and Cerebro spinal fluid (CSF). There are many segmentation techniques available based on parametric and non-parametric models. Among these models, segmentation of medical images based on parametric technique is more accurate. In model based segmentation, entire image is viewed as a collection of image region. Finite mixture models are utilized to characterize the pixel intensities inside the images. Hence, Finite Skew Gaussian Mixture model is used to carry out the segmentation process, the initial parameters are obtaining by using clustering algorithms and the updated equations are obtained by deriving the equations using EM algorithm. 288 pp. Englisch. Bestandsnummer des Verkäufers 9786139832828
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Segmentation of Medical MR Images Using Skew Gaussian Distribution
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vadaparthi NageshDr. Nagesh Vadaparthi is a Professor in the department of Information Technology, Maharaj Vijayaram Gajapathi Raj College of Engineering, India. He has published various papers in reputed National and International J. Bestandsnummer des Verkäufers 385873338
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Segmentation of Medical MR Images Using Skew Gaussian Distribution
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Segmentation of Medical MR Images Using Skew Gaussian Distribution
Verlag:
LAP LAMBERT Academic Publishing Jun 2018, 2018
ISBN 10: 6139832829
ISBN 13: 9786139832828
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Brain tumor is one of the major causes for the increase in mortality among the children and adults. In fact, tumor is a mass of tissue that grows-out of control from the normal forces which regulates growth. Therefore, identification of this in advance helps in the recovery of patients through suggestive and corrective treatments. To identify these brain diseases, it is essential to segment the brain tissues which consist of mainly three parts such as Gray Matter (GM), White Matter (WM) and Cerebro spinal fluid (CSF). There are many segmentation techniques available based on parametric and non-parametric models. Among these models, segmentation of medical images based on parametric technique is more accurate. In model based segmentation, entire image is viewed as a collection of image region. Finite mixture models are utilized to characterize the pixel intensities inside the images. Hence, Finite Skew Gaussian Mixture model is used to carry out the segmentation process, the initial parameters are obtaining by using clustering algorithms and the updated equations are obtained by deriving the equations using EM algorithm.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 288 pp. Englisch. Bestandsnummer des Verkäufers 9786139832828
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Segmentation of Medical MR Images Using Skew Gaussian Distribution
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ISBN 10: 6139832829
ISBN 13: 9786139832828
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Taschenbuch. Zustand: Neu. Segmentation of Medical MR Images Using Skew Gaussian Distribution | Nagesh Vadaparthi (u. a.) | Taschenbuch | 288 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139832828 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 113972593
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Brain tumor is one of the major causes for the increase in mortality among the children and adults. In fact, tumor is a mass of tissue that grows-out of control from the normal forces which regulates growth. Therefore, identification of this in advance helps in the recovery of patients through suggestive and corrective treatments. To identify these brain diseases, it is essential to segment the brain tissues which consist of mainly three parts such as Gray Matter (GM), White Matter (WM) and Cerebro spinal fluid (CSF). There are many segmentation techniques available based on parametric and non-parametric models. Among these models, segmentation of medical images based on parametric technique is more accurate. In model based segmentation, entire image is viewed as a collection of image region. Finite mixture models are utilized to characterize the pixel intensities inside the images. Hence, Finite Skew Gaussian Mixture model is used to carry out the segmentation process, the initial parameters are obtaining by using clustering algorithms and the updated equations are obtained by deriving the equations using EM algorithm. Bestandsnummer des Verkäufers 9786139832828
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