Segmentation of medical images by Using k-NN classifier on Field Programmable Logic Array (FPGA)

Image segmentation is one of the mostly used procedures in the medical image processing applications. Due to the high resolution characteristic of the medical images and a large amount of computational load in mathematical methods, medical image segmentation process has an excessive computation complexity. Recently, Field Programmable Gate Array (FPGA) implementation capable of performing many complex computations in parallel has been applied in many areas needed for high computation time. In this study, it is proposed that neighbour-pixel-intensity based feature extraction methods for extraction of the textural features in medical images, and k-NN classifier for segmentation process.