No abstract

Describes an automated approach to register CT and MR brain images. Differential operators in scale space are applied to each type of image data, so as to produce feature images depicting "ridgeness". The resulting CT and MR feature images show similarities which can be used for matching. No segmentation is needed and the method is devoid of human interaction. The matching is accomplished by hierarchical correlation techniques. Results of 2-D and 3-D matching experiments are presented. The correlation function ensures an accurate match even if the scanned volumes to be matched do not completely overlap, or if some of the features in the images are not similar.

We present a new VLIW core as a successor to the TriMedia TM1000. The processor is targeted for embedded use in media-processing devices like DTVs and set-top boxes. Intended as a core, its design must be supplemented with on-chip co-processors to obtain a cost-effective system. Good performance is obtained through a uniform 64-bit 5 issue-slot VLIW design, supporting subword parallelism with an extensive instruction set optimized with respect to media-processing. Multi-slot 'super-ops' allow powerful multi-argument and multi-result operations. As an example, an IDCT algorithm shows a very low instruction count in comparison with other processors. To achieve good performance, critical sections in the application program source code need to be rewritten with vector data types and function calls for media operations. Benchmarking with several media applications was used to tune the instruction set and study cache behavior. This resulted in a VLIW architecture with wide data paths and relatively simple cpu control.

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No abstract