Semantic Layers for Illustrative Volume Rendering

Rautek, Peter; Brückner, Stefan; Gröller, M. Eduard

doi:10.1109/tvcg.2007.70591

Cited by 59 publications

(27 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Higher-level user interfaces can be used to couple semantic expressions to parameters in the TF. Approaches include both principal component analysis of user input [99] and text based user input [94,96]. A natural form of interaction, which is explored, is to 'paint' the TF directly on the data [29,30,117] with a work flow that is reminiscent of the Photoshop imaging software.…”

Section: High-level Semantics and Work Flowmentioning

confidence: 99%

Medical Volume Visualization Beyond Single Voxel Values

Lindholm¹

2014

View full text Add to dashboard Cite

Acknowledgments AbstractMedical visualization involves many complex decisions for both the user and the imaging algorithms. This thesis aims to improve medical volume visualization through a series of technical contributions to aid such decision processes. Improvements are achieved by using more data, beyond single voxels, in the associated visual analyses.Simultaneous visualization of multiple data sources and different data formats is rapidly becoming a necessity. This is due to both the growing number of data producing image acquisition techniques as well as the increase in geometric data representations that can be created. Maintaining high rendering performance under these circumstances is challenging, but necessary, to support an exploratory visualization process. This thesis proposes two algorithms to address this challenge: a multi-volume approach that applies binary-space partitioning to solve painters' algorithm geometrically and a rendering algorithm for hybrid data that improves the management of the available graphics memory.Additional information for decision support is often derived from the captured image data. Classification techniques, in particular, often utilize secondary information sources or neighborhood analysis as means to improve specificity. One example is a proposed algorithm that improves visualization of blood vessels by automatically optimizing visualization parameters based on observed vesselness. This thesis also proposes algorithms involving neighborhood analysis, with a particular focus on domain specific classification knowledge provided by the user. One algorithm provides the ability to semantically state spatial relations between tissues based on encoded material information. Another algorithm improves the representation of discrete features by integrating the users' knowledge in the reconstruction step of the visualization pipeline.Many of the methods proposed in this thesis can also be applied to other domains, but are all described here in the context of medical volume visualization as most of the research has been performed within this field.v Populärvetenskaplig SammanfattningMedicinsk visualisering involverar en mängd komplexa beslut, både för användaren och för bildsystemet. I många fall handlar dessa beslut om vilken information som skall visas och hur den skall visas. Utfallen av dessa beslut kan potentiellt förbättras ju mer data som inkluderas i beslutsprocessen bortom enskilda voxlar. Den här avhandlingen avser att förbättra och effektivisera medicinsk volumsvisualisering genom en rad tekniska forskningsbidrag.Samtidig visualisering av multipla datakällor och olika dataformat är snabbt på väg att bli en nödvändighet. Dels på grund av det växande antalet dataproducerande bildmetoder, men även på grund av det stigande antalet geometriska representationer som kan skapas. Att producera snabba effektiva renderingar under dessa förutsättningar är svårt, men också nödvändigt för att stödja den ofta explorativa visualiseringsprocessen. Ytterligare information för besluts...

show abstract

Section: High-level Semantics and Work Flowmentioning

confidence: 99%

Medical Volume Visualization Beyond Single Voxel Values

Lindholm¹

2014

View full text Add to dashboard Cite

show abstract

“…Notice that content trans-coding process can be simplified by using semantics [Rautek and Bruckner 2007]. Knowing user context [Yoon et al 2007] [Mowafi and Zhang 2007] [Kaltz 2006] is then required in order to choose the transmission channel with a user-centered interface approach.…”

Section: Related Workmentioning

confidence: 99%

Context aware, multimodal, and semantic rendering engine

Salamin

Thalmann

Vexo

2009

Proceedings of the 8th International Conference on Virtual Reality Continuum and Its Applications in Industry

View full text Add to dashboard Cite

Figure 1: An example of trans-modal rendering application selected by our engine to render 3D digital content to visually impaired people. AbstractNowadays, several techniques exist to render digital content such as graphics, audio, haptic, etc. Unfortunately, they require different faculties that cannot always be applied, e.g. providing a picture to a blind person would be useless.In this paper, we present a new multimodal rendering engine with a server web-connected to other devices to perform ubiquitous computing. In order to take advantage of user capabilities, we defined an ontology populated with the following elements: user, device, and information. Our system, with the help of this ontology, aims to select and launch automatically a rendering application.Several test case applications were implemented to render shape, text, and video information via audio, haptic, and sight channels. Validations demonstrate that our system is flexible, easily extensible, and shows promise.

show abstract

“…The derivation of the defuzzyfication as described in earlier work [RBG07] is essential for the implementation of the fuzzy logic on the GPU. We briefly review this derivation: For defuzzyfication we want to find the centroid of the aggregated function.…”

Section: Implication Aggregation and Defuzzificationmentioning

confidence: 99%

“…In earlier work [RBG07] the use of data and illustration semantics was introduced for illustrative volume rendering. In this paper we extend this approach with the following main contributions:…”

Section: Introductionmentioning

confidence: 99%