Efficient Brain MRI Segmentation Algorithm on TK1

In the past decades, image processing technologies have been applied to process medical images. Usually, image segmentation is an important strategy. Fuzzy c-means clustering algorithm has been wildly used for segmentation of brain magnetic resonance image. In the paper, we implement a genetic Fuzzy c-means clustering algorithm based on embedded graphic process units system, NVIDIA TK1, to accelerate computation speed of time-consuming on segmenting brain magnetic resonance image. The experimental results show that the proposed algorithm not only can used to analyze such image on cheap device but also gains from the performance.