Name
Abstract | ||
|---|---|---|
Rendering tomographic data sets is a computationally expensive task, and often accomplished using hardware acceleration. The data sets are usually anisotropic as a result of the process used to acquire them. A vital part of rendering them is the conversion of the discrete signal back into a continuous one, via interpolation. On graphics hardware, this is often achieved via simple linear interpolation. We present a novel approach for real-time anisotropic volume data interpolation on a graphics processing unit and draw comparisons to standardized interpolation alternatives. Our approach uses a pre-computed set of cross-slice correspondences to compensate for missing data. We perform a qualitative analysis using sparse data sets, investigating both visual quality, as well divergence from the ground truth, testing the limits of the interpolation method. Our method produces high quality interpolation with a moderate performance impact compared to alternatives. It is ideal for reconstructing sparse data sets, as well as minimizing quality loss while scaling large amounts of data to fit on most mobile graphics cards. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2448531.2448533 | SCCG |
Keywords | Field | DocType |
high quality interpolation,real-time anisotropic volume data,missing data,graphics hardware,sparse data set,interpolation method,simple linear interpolation,tomographic data set,registration-based interpolation real-time volume,standardized interpolation alternative,volume rendering,interpolation,real time | Computer vision,Nearest-neighbor interpolation,Multivariate interpolation,Computer science,Interpolation,Stairstep interpolation,Theoretical computer science,Artificial intelligence,Linear interpolation,Trilinear interpolation,Image scaling,Bilinear interpolation | Conference |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lasse Farnung Laursen | 1 | 2 | 1.06 |
| Hildur Ólafsdóttir | 2 | 41 | 6.12 |
| Jakob Andreas Bærentzen | 3 | 58 | 7.67 |
| Michael Sass Hansen | 4 | 41 | 5.78 |
| Bjarne Kjær Ersbøll | 5 | 10 | 3.63 |