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Fiber tracking is a technique that determines the location of fiber bundles in a human brain. Sequential implementations of fiber tracking usually require a large execution time, which hinders both the interactivity currently experienced by physicians and its applications to large collections of data sets. In this paper we present the design and implementation of fiber tracking applications in two different parallel environments, GPUs and PC clusters. The performance results obtained in our experiments show that both HPC configurations are suitable for fiber tracking: GPUs for interactive applications targeted at physicians and PC clusters for batch processing by fiber tracking researchers.