Cinar, SalimKurnaz, Mehmet Nadir2019-08-012019-08-012013978-1-4577-0216-71557-170Xhttps://hdl.handle.net/11480/443835th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC) -- JUL 03-07, 2013 -- Osaka, JAPANImage segmentation is one of the mostly used procedures in the medical image processing applications. Due to the high resolution characteristics of the medical images and a large amount of computational load in mathematical methods, medical image segmentation process has an excessive computational complexity. Recently, FPGA implementation has been applied in many areas due to its parallel processing capability. In this study, neighbor-pixel-intensity based method for feature extraction and Grow and Learn (GAL) network for segmentation process are proposed. The proposed method is comparatively examined on both PC and FPGA platforms.eninfo:eu-repo/semantics/closedAccessConference Object4070407324110626WOS:000341702104129N/A