Volume rendering techniques can be powerful tools when visualizing medical data sets. The characteristics of being able to capture 3-D internal structures make the technique attractive. Scanning equipment is producing medical images, with rapidly increasing resolution, resulting in heavily increased size of the data set. Despite the great amount of processing power CPUs deliver, the required precision in image quality can be hard to obtain in real-time rendering. Therefore, it is highly desirable to optimize the rendering process. Modern GPUs possess much more computational power and is available for general purpose programming through high level shading languages. Efficient representations of the data are crucial due to the limited memory provided by the GPU. This thesis describes the theoretical background and the implementation of an approach presented by Patric Ljung, Claes Lundström and Anders Ynnerman at Linköping University. The main objective is to implement a fully working multi-resolution framework with two separate pipelines for pre-processing and real-time rendering, which uses the GPU to visualize large medical data sets.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-10715 |
| Date | January 2008 |
| Creators | Towfeek, Ajden |
| Publisher | Linköpings universitet, Institutionen för teknik och naturvetenskap, Institutionen för teknik och naturvetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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