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Parametric surfaces are an essential modeling tool in computer aided design and movie production. Even though their use is well established in industry, generating ray-traced images adds significant cost in time and memory consumption. Ray tracing such surfaces is usually accomplished by subdividing the surfaces on-the-fly, or by conversion to a polygonal representation. However, on-the-fly subdivision is computationally very expensive, whereas polygonal meshes require large amounts of memory. This is a particular problem for parametric surfaces with displacement, where very fine tessellation is required to faithfully represent the shape. Hence, memory restrictions are the major challenge in production rendering. In this paper, we present a novel solution to this problem. We propose a compression scheme for a-priori Bounding Volume Hierarchies (BVHs) on parametric patches, that reduces the data required for the hierarchy by a factor of up to 48. We further propose an approximate evaluation method that does not require leaf geometry, yielding an overall reduction of memory consumption by a factor of 60 over regular BVHs on indexed face sets and by a factor of 16 over established state-of-the-art compression schemes. Alternatively, our compression can simply be applied to a standard BVH while keeping the leaf geometry, resulting in a compression rate of up to 2:1 over current methods. Although decompression generates additional costs during traversal, we can manage very complex scenes even on the memory restrictive GPU at competitive render times.
Extracorporeal membrane oxygenation (ECMO) was established as a treatment for severe cardiac or respiratory disease. Intra-device clot formation is a common risk. This is based on complex coagulation phenomena which are not yet sufficiently understood. The objective was the development and validation of a methodology to capture the key properties of clots deposed in membrane lungs (MLs), such as clot size, distribution, burden, and composition. One end-oftherapy PLS ML was examined. Clot detection was performed using multidetector computed tomography (MDCT), microcomputed tomography (μCT), and photography of fiber mats (fiber mat imaging, FMI). Histological staining was conducted for von Willebrand factor (vWF), platelets (CD42b, CD62P), fibrin, and nucleated cells (4′, 6-diamidino-2-phenylindole, DAPI). The three imaging
methods showed similar clot distribution inside the ML. Independent of the imaging method, clot loading was detected predominantly in the inlet chamber of the ML. The μCT had the highest accuracy. However, it was more expensive and time consuming than MDCT or FMI. The MDCT detected the clots with low scanning time. Due to its lower resolution, it only showed clotted areas but not
the exact shape of clot structures. FMI represented the simplest variant, requiring little effort and resources. FMI allowed clot localization and calculation of clot volume. Histological evaluation indicated omnipresent immunological deposits throughout the ML. Visually clot-free areas were covered with leukocytes and platelets forming platelet-leukocyte aggregates (PLAs). Cells were embedded in vWF cobwebs, while vWF fibers were negligible. In conclusion, the presented
methodology allowed adequate clot identification and histological classification
of possible thrombosis markers such as PLAs.