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stefanbanev

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About stefanbanev

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  1. Artificial volumetric data usually contain a way more homogeneous regions than data from CT/MRI scanner thus, adaptive algorithms could provide a quite dramatic performance boost; in fact, the typical speedup for CT/MRI data is around 20..30 times for the CT/MRI data for the similar quality. Such result for adaptive volumetric ray casting has been demonstrated only for multi-core CPU hardware so to have a similar development for GPU should be quite an impressive breakthrough in the area.   Btw, "marching cubes" has nothing to do with volume rendering it is just a mesh generation from volumetric data. In fact, marching cubes is the way how to avoid volume rendering to retreat to render polygons what GPU does the best. It's correct that the multi shelled mesh generation for different levels of isosurfaces may allow to approximate a rendering integral to have a true volume rendering output but it is excessively more computationally expensive to sustain the same level of integral precision then to do it directly especially if Transfer Function interactive modification is a requirement. The sampling rate ~x16 samples per cell for Interpolation Classification VR is the sampling density to ensure a high quality rendering for medical applications; apparently so many levels of meshes makes this technique impractical for general VR application BUT it may be useful to visualise a small volumetric objects for games (besides, the high precision is not a requirement for game). 
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