Low resource processing algorithms for laser Doppler blood flow imaging

The emergence of full field laser Doppler blood flow imaging systems based on CMOS camera technology means that a large amount of data from each pixel in the image needs to be processed rapidly and system resources need to be used efficiently. Conventional processing algorithms that are utilized in single point or scanning systems are therefore not an ideal solution as they will consume too much system resource. Two processing algorithms that address this problem are described and efficiently implemented in a field programmable gate array. The algorithms are simple enough to use low system resource but effective enough to produce accurate flow measurements. This enables the processing unit to be integrated entirely in an embedded system, such as in an application-specific integrated circuit. The first algorithm uses a short Fourier transformation length (typically 8) but averages the output multiple times (typically 128). The second method utilizes an infinite impulse response filter with a low number of filter coefficients that operates in the time domain and has a frequency-weighted response. The algorithms compare favorably with the reference standard 1024 point fast Fourier transform in terms of both resource usage and accuracy. The number of data words per pixel that need to be stored for the algorithms is 1024 for the reference standard, 8 for the short length Fourier transform algorithm and 5 for the algorithm based on the infinite impulse response filter. Compared to the reference standard the error in the flow calculation is 1.3% for the short length Fourier transform algorithm and 0.7% for the algorithm based on the infinite impulse response filter.