9783659742002 - A Handbook on Computerized Tumor Classification from MRI of Brain: Clear, Concise, Easy-to Read Guide di Roy, Sudipta; Bandyopadhyay, Samir Kumar (5 risultati)

Taschenbuch. Condizione: Neu. A Handbook on Computerized Tumor Classification from MRI of Brain | Clear, Concise, Easy-to Read Guide | Sudipta Roy (u. a.) | Taschenbuch | 128 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659742002 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Early detection of the brain tumor in the brain magnetic resonance imaging is important because physician needs to quantification and classify of the tumor and its area. The computer and image processing techniques can provide great help in analyzing the tumor area and its type by classification. On the other side, computer-aided detection (CAD) has been developing fast in the last two decades. The main idea of CAD is to assist radiologists in interpreting medical images by using dedicated computer systems to provide 'Accurate System'. Studies on CAD systems and technology show that CAD can help to improve diagnostic accuracy of radiologists, lighten the burden of increasing workload, reduce cancer missed due to fatigue, overlooked or data overloaded and improve inter- and intra-reader variability. The final medical decision is made by the radiologists. Consequently, radiologists expect that CAD systems can improve their diagnostic abilities based on synergistic effects between the radiologist and the computer with medical image analysis and machine learning techniques. 128 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Roy SudiptaSudipta Roy is pursuing Ph.D.(Tech) in the field of image processing from Dept. of CSE, University of Calcutta (C.U), Kolkata, India from 2014. He received his B.Tech and M.Tech degree in the Dept. of Computer Science & E.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Early detection of the brain tumor in the brain magnetic resonance imaging is important because physician needs to quantification and classify of the tumor and its area. The computer and image processing techniques can provide great help in analyzing the tumor area and its type by classification. On the other side, computer-aided detection (CAD) has been developing fast in the last two decades. The main idea of CAD is to assist radiologists in interpreting medical images by using dedicated computer systems to provide 'Accurate System'. Studies on CAD systems and technology show that CAD can help to improve diagnostic accuracy of radiologists, lighten the burden of increasing workload, reduce cancer missed due to fatigue, overlooked or data overloaded and improve inter- and intra-reader variability. The final medical decision is made by the radiologists. Consequently, radiologists expect that CAD systems can improve their diagnostic abilities based on synergistic effects between the radiologist and the computer with medical image analysis and machine learning techniques.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Early detection of the brain tumor in the brain magnetic resonance imaging is important because physician needs to quantification and classify of the tumor and its area. The computer and image processing techniques can provide great help in analyzing the tumor area and its type by classification. On the other side, computer-aided detection (CAD) has been developing fast in the last two decades. The main idea of CAD is to assist radiologists in interpreting medical images by using dedicated computer systems to provide 'Accurate System'. Studies on CAD systems and technology show that CAD can help to improve diagnostic accuracy of radiologists, lighten the burden of increasing workload, reduce cancer missed due to fatigue, overlooked or data overloaded and improve inter- and intra-reader variability. The final medical decision is made by the radiologists. Consequently, radiologists expect that CAD systems can improve their diagnostic abilities based on synergistic effects between the radiologist and the computer with medical image analysis and machine learning techniques.