Registration-based interpolation real-time volume visualization

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.