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Abstract / Description of output
Significance: Diffuse correlation spectroscopy (DCS) is an indispensable tool for quantifying cerebral blood flow noninvasively by measuring the autocorrelation function (ACF) of the diffused light. Recently, a multispeckle DCS approach was proposed to scale up the sensitivity with the number of independent speckle measurements, leveraging the rapid development of single-photon avalanche diode (SPAD) cameras. However, the extremely high data rate from advanced SPAD cameras is beyond the data transfer rate commonly available and requires specialized high-performance computation to calculate large number of autocorrelators (ACs) for real-time measurements. Aim: We aim to demonstrate a data compression scheme in the readout field-programmable gate array (FPGA) of a large-pixel-count SPAD camera. On-FPGA, data compression should democratize SPAD cameras and streamline system integration for multispeckle DCS. Approach: We present a formula presented SPAD array with 128 linear ACs embedded on an FPGA to calculate 12,288 ACFs in real time. Results: We achieved a signal-to-noise ratio (SNR) gain of 110 over a single-pixel DCS system and more than threefold increase in SNR with respect to the state-of-the-art multispeckle DCS. Conclusions: The FPGA-embedded autocorrelation algorithm offers a scalable data compression method to large SPAD array, which can improve the sensitivity and usability of multispeckle DCS instruments.
Keywords / Materials (for Non-textual outputs)
- Data Compression
- Signal-To-Noise Ratio
- Spectrum Analysis
- diffuse correlation spectroscopy
- single-photon avalanche diode
- field-programmable gate array compression
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- 1 Finished
1/04/20 → 6/12/22