Traditionally, diffuse correlation spectroscopy (DCS) derives blood flow (BF) by measuring of the temporal intensity fluctuations of multiply scattered light from a single source-detector pair. In this paper, a multi-wavelength DCS approach was proposed to quantify tissue blood flow and scattering coefficient based on long short-term memory (LSTM) architecture. Phantom experiments were established to measure normalized intensity autocorrelation function data by multi-wavelength DCS system at different velocities and scattering coefficients. The results support the notion of using proposed LSTM architecture for quantification of blood flow and scattering coefficient in DCS.
Hypertension and other cardio-cerebrovascular diseases seriously endanger human life and health. Pulse wave and blood flow are the main parameters reflecting blood pressure and other physiological and pathological conditions of cardiovascular system . Fast diffusion correlation spectroscopy (fast DCS) based on software correlator is constructed on the basis of the traditional diffusion correlation spectroscopy (DCS), which greatly improves the sampling frequency of blood flow. Compared with the traditional DCS frequency of 2-3 Hz, the sampling frequency of fast DCS is as high as 30 Hz, so that the corresponding pulse wave information can be obtained while realizing the fast measurement of blood flow. In this paper, we employed two complimentary methods to measure blood flow and pulse wave from one healthy subjects: fast DCS and color doppler ultrasound (CDUs). Measures of blood flow derived using fast DCS and CDUs due to an arterial occlusion were well correlated (R=0.7218, p< 0.01). This study supports that fast DCS can quickly and accurately measure the main parameters of physiological and pathological conditions of cardiovascular system such as pulse wave and blood flow, and provides a convenient and rapid method for providing good diagnosis and treatment evaluation for cardio-cerebrovascular diseases.
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