Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. Physics-based visualization of tensor fields has proven to
show the main features of symmetric second-order tensor fields, while still displaying the most important information of the data, namely the main directions in medical diffusion tensor data using texture and additional attributes using color-coding, in a continuous representation. Nevertheless, its application and usability remains limited due to its computational expensive and sensitive nature.
We introduce a novel approach to compute a fabric-like texture pattern from tensor fields on arbitrary non-selfintersecting surfaces that is motivated by image space line integral convolution (LIC). Our main focus lies on regaining three-dimensionality of the data under user interaction, such as rotation and scaling. We employ a multi-pass rendering approach to estimate proper modification of the LIC noise input texture to support the three-dimensional perception during user interactions.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:16526 |
| Date | 20 October 2017 |
| Creators | Eichelbaum, Sebastian |
| Contributors | Scheuermann, Gerik, Universität Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | urn:nbn:de:bsz:15-qucosa2-163403, qucosa:16340 |
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