A field programmable gate array implementation for biomedical system-on-chip (SoC)

Medical imaging has become essential in health industry. It becomes crucial during on-line or off-line data transmission between healthcare institutions. Larger image requires more spaces to be saved and more time to be loaded. Thus, in this paper, an artificial neural network is chosen to quantize the image into smaller number of colour palettes to reduce its size. A modified Kohonen Self-Organizing Maps algorithm is applied for hardware implementation. The Euclidean calculation in typical Kohonen algorithm is replaced with Manhattan Distance calculation to accelerate the computation in hardware implementation. In this research, the KSOM Processing Element CoProcessor hardware implementation, it consists of two main modules namely Datapath Unit (DPU) module and Control Unit (CU) module. The coprocessor is tested with one RGB colour input and three initial weights or desired palettes with three iterations. From the simulation testing, it took 480 nanoseconds to complete three iterations.