9786139970469 - Optimal Multilevel Threshold Selection for Brain MR Image Segmentation: Optimal MR Image Thresholding using bio and nature inspired algorithms di Injeti, Satish Kum... (7 risultati)

Paperback. Condizione: Brand New. 96 pages. 8.66x5.91x0.24 inches. In Stock.

Taschenbuch. Condizione: Neu. Optimal Multilevel Threshold Selection for Brain MR Image Segmentation | Optimal MR Image Thresholding using bio and nature inspired algorithms | Satish Kumar Injeti (u. a.) | Taschenbuch | 96 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139970469 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing. 96 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Injeti Satish KumarDr. Satish Kumar Injeti was Assistant Professor in Electrical Engineering, National Institute of Technology Warangal, Telengana State, India. He received her B.Tech., M.Tech., and Ph.D. from JNTU Hyderabad, JNTU An.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Medical image processing is one of the real research regions in the most recent four decades. Segmentation partitions an image into constituent parts. This basic operation helps to analyze and interpret a certain region of interest of an image. Image segmentation helps in diagnosing abnormality in brain or any part of the body from the MRI scan or PET scan. Presently MRI is the most popular clinical diagnostic procedure for detection of any brain disorder, as it is a complete non-invasive method. Moreover, its ability to produce high resolution spatial images and its sensitivity towards differentiating neurological tissues help in diagnosis, prognosis, pre-surgical and post-surgical treatment planning for various diseases. If image segmentation can be done in an effective way, then the lesions, or the disorder, if present, can be classified to an effectual micro-level. This book presents a fast and efficient nature inspired optimization approaches for the optimal selection of threshold levels for brain MR image pre segmentation. We hope this book is most useful for the researchers and masters level students who were in the area of digital image processing.