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The formulation of the FBA in the form of a CA is simple, efficient and straightforward, and can be implemented in low cost vendor-independent graphics hardware. The method can efficiently be applied to perform organ segmentation and quantitative evaluation in clinical routine.

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In this paper we describe a cellular automaton (CA) used to perform the watershed transform in N-D images. Our method is based on image integration via the Ford-Bellman shortest paths algorithm. Due to the local nature of CA algorithms we show that they are designed to run on massively parallel processors and therefore, be efficiently implemented on low cost consumer graphical processing units (GPUs).