Soumya ghose (10 risultati)

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Taschenbuch. Condizione: Neu. Prostate Segmentation in Ultrasound and Magnetic Resonance Images | Soumya Ghose (u. a.) | Taschenbuch | 152 S. | Englisch | 2016 | Scholars' Press | EAN 9783659838453 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonance images (MRI) facilitates volume estimation, multi-modal image registration, surgical planing and image guided prostate biopsies. The objective of this work was to develop shape and region prior deformable models for accurate, robust and computationally efficient prostate segmentation in TRUS and MRI images. Primary contribution of this work was in adopting a probabilistic learning approach to achieve soft classification of the prostate for automatic initialization and evolution of a shape and region prior deformable models for prostate segmentation in TRUS images. Region based energy was determined from region based statistics of the posterior probabilities. Graph cut energy minimization framework was adopted for prostate segmentation in MRI. Posterior probabilities obtained in a supervised learning schema and from a probabilistic segmentation of the prostate using an atlas are fused in logarithmic domain to reduce segmentation error. Finally a graph cut energy minimization in the stochastic framework achieves prostate segmentation in MRI. 152 pp. Englisch.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ghose SoumyaDr. Soumya Ghose is senior research associate in the Department of Biomedical Engineering at Case Western Reserve University. His research interest includes machine learning, medical image segmentation and registration. P.…

Condizione: New. Print on Demand.

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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonance images (MRI) facilitates volume estimation, multi-modal image registration, surgical planing and image guided prostate biopsies. The objective of this work was to develop shape and region prior deformable models for accurate, robust and computationally efficient prostate segmentation in TRUS and MRI images. Primary contribution of this work was in adopting a probabilistic learning approach to achieve soft classification of the prostate for automatic initialization and evolution of a shape and region prior deformable models for prostate segmentation in TRUS images. Region based energy was determined from region based statistics of the posterior probabilities. Graph cut energy minimization framework was adopted for prostate segmentation in MRI. Posterior probabilities obtained in a supervised learning schema and from a probabilistic segmentation of the prostate using an atlas are fused in logarithmic domain to reduce segmentation error. Finally a graph cut energy minimization in the stochastic framework achieves prostate segmentation in MRI.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonance images (MRI) facilitates volume estimation, multi-modal image registration, surgical planing and image guided prostate biopsies. The objective of this work was to develop shape and region prior deformable models for accurate, robust and computationally efficient prostate segmentation in TRUS and MRI images. Primary contribution of this work was in adopting a probabilistic learning approach to achieve soft classification of the prostate for automatic initialization and evolution of a shape and region prior deformable models for prostate segmentation in TRUS images. Region based energy was determined from region based statistics of the posterior probabilities. Graph cut energy minimization framework was adopted for prostate segmentation in MRI. Posterior probabilities obtained in a supervised learning schema and from a probabilistic segmentation of the prostate using an atlas are fused in logarithmic domain to reduce segmentation error. Finally a graph cut energy minimization in the stochastic framework achieves prostate segmentation in MRI.…