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Samuel Voß

dblp:170/7152 · DBLP profile ↗
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5ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-9757-7564ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 5 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › information visualization
composite visualization
0.312017
Combined Visualization of Vessel Deformation and Hemodynamics in Cerebral Aneurysms · IEEE Trans. Vis. Comput. Graph. 2017

Methods — techniques the papers use, named apart from their topics

glyph-based visualization · 0.6GPU rendering · 0.62.5d and 3d linked views · 0.6
YearPublicationVenuePosition
2021 Skyscraper visualization of multiple time-dependent scalar fields on surfaces
Monique Meuschke, Samuel Voß, Franziska Gaidzik, Bernhard Preim, Kai Lawonn
Comput. Graph.2
2018 Exploration of blood flow patterns in cerebral aneurysms during the cardiac cycle
Monique Meuschke, Samuel Voß, Bernhard Preim, Kai Lawonn
Comput. Graph.2
2017 Virtual Inflation of the Cerebral Artery Wall for the Integrated Exploration of OCT and Histology Data
abstract
Abstract Intravascular imaging provides new insights into the condition of vessel walls. This is crucial for cerebrovascular diseases including stroke and cerebral aneurysms, where it may present an important factor for indication of therapy. In this work, we provide new information of cerebral artery walls by combining ex vivo optical coherence tomography (OCT) imaging with histology data sets. To overcome the obstacles of deflated and collapsed vessels due to the missing blood pressure, the lack of co‐alignment as well as the geometrical shape deformations due to catheter probing, we developed the new image processing method virtual inflation. We locally sample the vessel wall thickness based on the (deflated) vessel lumen border instead of the vessel's centerline. Our method is embedded in a multi‐view framework where correspondences between OCT and histology can be highlighted via brushing and linking yielding OCT signal characteristics of the cerebral artery wall and its pathologies. Finally, we enrich the data views with a hierarchical clustering representation which is linked via virtual inflation and further supports the deduction of vessel wall pathologies.
Sylvia Saalfeld, Thomas Hoffmann 0002, Axel Boese, Samuel Voß, Thomas Kalinski, Martin Skalej, Bernhard Preim
Comput. Graph. Forum4
2017 Glyph-Based Comparative Stress Tensor Visualization in Cerebral Aneurysms
abstract
Abstract We present the first visualization tool that enables a comparative depiction of structural stress tensor data for vessel walls of cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. Medical researchers emphasize the importance of analyzing the interaction of morphological and hemodynamic information for the patient‐specific rupture risk evaluation and treatment analysis. Tensor data such as the stress inside the aneurysm walls characterizes the interplay between the morphology and blood flow and seems to be an important rupture‐prone criterion. We use different glyph‐based techniques to depict local stress tensors simultaneously and compare their applicability to cerebral aneurysms in a user study. We thus offer medical researchers an effective visual exploration tool to assess the aneurysm rupture risk. We developed a GPU‐based implementation of our techniques with a flexible interactive data exploration mechanism. Our depictions are designed in collaboration with domain experts, and we provide details about the evaluation.
Monique Meuschke, Samuel Voß, Oliver Beuing, Bernhard Preim, Kai Lawonn
Comput. Graph. Forum2
2017 Combined Visualization of Vessel Deformation and Hemodynamics in Cerebral Aneurysms
abstract
We present the first visualization tool that combines patient-specific hemodynamics with information about the vessel wall deformation and wall thickness in cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. For the patient-specific rupture risk evaluation and treatment analysis, both morphological and hemodynamic data have to be investigated. Medical researchers emphasize the importance of analyzing correlations between wall properties such as the wall deformation and thickness, and hemodynamic attributes like the Wall Shear Stress and near-wall flow. Our method uses a linked 2.5D and 3D depiction of the aneurysm together with blood flow information that enables the simultaneous exploration of wall characteristics and hemodynamic attributes during the cardiac cycle. We thus offer medical researchers an effective visual exploration tool for aneurysm treatment risk assessment. The 2.5D view serves as an overview that comprises a projection of the vessel surface to a 2D map, providing an occlusion-free surface visualization combined with a glyph-based depiction of the local wall thickness. The 3D view represents the focus upon which the data exploration takes place. To support the time-dependent parameter exploration and expert collaboration, a camera path is calculated automatically, where the user can place landmarks for further exploration of the properties. We developed a GPU-based implementation of our visualizations with a flexible interactive data exploration mechanism. We designed our techniques in collaboration with domain experts, and provide details about the evaluation.
Monique Meuschke, Samuel Voß, Oliver Beuing, Bernhard Preim, Kai Lawonn
IEEE Trans. Vis. Comput. Graph.2