5 results match your criteria: "VRVis Research Center for Virtual Reality and Visualization[Affiliation]"

Current European flood-rich period exceptional compared with past 500 years.

Nature

July 2020

Department of Economic, Social and Environmental History, Institute of History, University of Bern, Bern, Switzerland.

There are concerns that recent climate change is altering the frequency and magnitude of river floods in an unprecedented way. Historical studies have identified flood-rich periods in the past half millennium in various regions of Europe. However, because of the low temporal resolution of existing datasets and the relatively low number of series, it has remained unclear whether Europe is currently in a flood-rich period from a long-term perspective.

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Purpose: Virtual endoscopy has already proven its benefit for pre-operative planning of endoscopic pituitary surgery. The translation of such a system into the operating room is a logical consequence, but only a few general intra-operative image guided systems providing virtual endoscopic images have been proposed so far. A discussion of related visualization and interaction problems occurring during sinus and pituitary surgery is still missing.

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In order to robustly match a statistical model of shape and appearance (e.g. AAM) to an unseen image, it is crucial to employ a robust model fittness measure.

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Objective: Volume segmentation with concurrent visualization is becoming an increasingly important part of medical diagnostics. This is due to the fact that the immediate visual feedback speeds up evaluation of the segmentation process, hence enhances segmentation quality. Therefore, our aim was to develop a method for volume segmentation and smoothing which achieves interactive performance on standard PCs and is useful in clinical practice (i.

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Quality of segmentations obtained by 3D Active Appearance Models (AAMs) crucially depends on underlying training data. MRI heart data, however, often come noisy, incomplete, with respiratory-induced motion, and do not fulfill necessary requirements for building an AAM. Moreover, AAMs are known to fail when attempting to model local variations.

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