A Hardware Implementation of a Levelset Algorithm for Carotid Lumen Segmentation in CTA

This work presents a novel hardware implementation of a levelset algorithm for carotid lumen segmentation in computed tomography. We propose to use a field programmable gate array (FPGA) to iteratively solve the underlying finite difference scheme. A FPGA processor can be programmed to have a dedicated hardware architecture including specific data path and processor core design with different types of parallelizations which is fully tailored and optimized toward its application. The method has been applied to ten carotid bifurcation of six stroke patients and the results have been compared to the results obtained from the same method implemented in C++. Visual inspections revealed similar segmentation results. The average computation time in software was 1663 A,A+- 86 seconds, the computation time on the FPGA processor was 28 seconds yielding approximately a 60-fold speed-up which to our knowledge has been unmmatched before for this class of algorithms.