9786138827481 - Analysis of Cardiac MRI to recognize cardiovascular disease by AST von Kayte, Jaypalsing; Deshmukh, Ratnadeep R.; N. Kayte, Charansing (9 Ergebnisse)

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Taschenbuch. Zustand: Neu. Analysis of Cardiac MRI to recognize cardiovascular disease by AST | Jaypalsing Kayte (u. a.) | Taschenbuch | 108 S. | Englisch | 2019 | Scholars' Press | EAN 9786138827481 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We are presenting a framework for the analysis of cardiac MRI to recognise cardiovascular diseases using Simple Iterative Object Extraction Techniques (SIOX) for Semi-Automatic Segmentation. This is one kind of segmentation methodology, in which the user outlines the region of interest with the mouse clicks and algorithms are applied so that the path that best fits the edge of the image is shown. SIOX techniques are used in this kind of segmentation. In an alternative kind of Semi-Automatic Segmentation, the algorithms return a spatial-taxon (i.e. foreground, object-group, object or object-part) selected by the user or designated via prior probabilities. The first contribution involves the introduction of a new algorithm for fitting 3-D Shape and Binary Mask of Endo and Epi Segmentation on cardiac MRI, using the inverse compositional image alignment algorithm. The observe 73 - double increase in fitting speed and accuracy that is on balance with Gauss-Newton Optimization. We show the high-quality results that are derived by the use of and KNN and describe the ways in which it could improve the automated analysis of medical images. 108 pp. Englisch.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kayte JaypalsingJaypalsing N. Kayte is currently pursuing the PhD degree in Computer Science and IT from the Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra India. He is cu.

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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -We are presenting a framework for the analysis of cardiac MRI to recognise cardiovascular diseases using Simple Iterative Object Extraction Techniques (SIOX) for Semi-Automatic Segmentation. This is one kind of segmentation methodology, in which the user outlines the region of interest with the mouse clicks and algorithms are applied so that the path that best fits the edge of the image is shown. SIOX techniques are used in this kind of segmentation. In an alternative kind of Semi-Automatic Segmentation, the algorithms return a spatial-taxon (i.e. foreground, object-group, object or object-part) selected by the user or designated via prior probabilities. The first contribution involves the introduction of a new algorithm for fitting 3-D Shape and Binary Mask of Endo and Epi Segmentation on cardiac MRI, using the inverse compositional image alignment algorithm. The observe 73 - double increase in fitting speed and accuracy that is on balance with Gauss-Newton Optimization. We show the high-quality results that are derived by the use of and KNN and describe the ways in which it could improve the automated analysis of medical images.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We are presenting a framework for the analysis of cardiac MRI to recognise cardiovascular diseases using Simple Iterative Object Extraction Techniques (SIOX) for Semi-Automatic Segmentation. This is one kind of segmentation methodology, in which the user outlines the region of interest with the mouse clicks and algorithms are applied so that the path that best fits the edge of the image is shown. SIOX techniques are used in this kind of segmentation. In an alternative kind of Semi-Automatic Segmentation, the algorithms return a spatial-taxon (i.e. foreground, object-group, object or object-part) selected by the user or designated via prior probabilities. The first contribution involves the introduction of a new algorithm for fitting 3-D Shape and Binary Mask of Endo and Epi Segmentation on cardiac MRI, using the inverse compositional image alignment algorithm. The observe 73 - double increase in fitting speed and accuracy that is on balance with Gauss-Newton Optimization. We show the high-quality results that are derived by the use of and KNN and describe the ways in which it could improve the automated analysis of medical images.