Functional near-infrared spectroscopy (fNIRS) is a powerful clinical tool for monitoring hemoglobin concentration in brain tissues by analyzing absorption of scattered light. Since human brain is composed of multilayers including scalp, skull, and cerebral cortex, fNIRS signals need be analyzed with a multilayer tissue model. However, retrieving the optical properties of a multilayer tissue is often difficult because nonlinear fitting of absorption parameters from a scattered light signal by a tissue is ill-posed especially when the signal level is low. In this paper we introduce the cost function based masking technique for effective error minimization in the nonlinear fitting of fNIRS signals. We have shown that this method effectively reduces the influences of measurement errors with a newly defined cost function. Numerically simulated fNIRS data were generated for a two-layered tissue model and are used to extract the optical parameters of the two-layered tissue model. Accuracies of extracted parameters were compared with and without our proposed cost function.
We have investigated distortions in the axial position calculations of a sample in lens-free digital inline holography (LDIH). Three-dimensional structure of a sample can be accurately obtained through a series of processes in LDIH, Fourier-domain digital filtering, and numerical focusing. The axial information of a sample is calculated through numerical beam propagation using diffraction theory and can be easily distorted because of approximations and assumptions used in the diffraction formula and the numerical beam propagation analysis used in LDIH. Since the reference light in LDIH is normally a diverging spherical beam from a point source, axial information of a sample calculated by a numerical focusing algorithm with a plane reference beam is off from the real axial position of a sample. We propose an algorithm that can correct this distortion in LDIH.
We have simulated the effects of the number of bits and the sampling rate of a digitizer on the performance of lifetime measurements. We found that the number of bits of a digitizer is important to obtain certain accuracy in lifetime measurement. There exists a certain critical sampling frequency of a digitizer required to separate a certain lifetime differences in a double exponentially decaying intensity profile. We did these simulations by using Monte Carlo simulations with least-square curve fitting algorithms.
Angles of polygon scanners have been measured by using rotary encoders, autocollimators or indexing tables. These methods produce precise angle values but require removal of polygon mirror from its motor. For resolving this inconvenience, we introduce a simple angle measurement method by measuring timing jitters of a scanned beam in the time-domain with a high-speed detector and a digitizer while a polygon scanner is rotating at its full speed. Our setup includes a 635 nm wavelength semiconductor laser, a high-speed photodiode, two lenses, and a high-speed digitizer. A polygon scanner with 12 facets were tested with a rotating frequency of near 350 Hz. To detect the signal of the photodiode, we used a high speed digitizer which has a sampling rate of 2Gs/s with 256MB on-board memory. We obtained repeated pulsed sequential photodiode signals for 12 mirror facets of the scanner. Angle variations and their jitters for 12 scanner mirror facets were successfully calculated from measured data. We have repeated same experiments with a photomultiplier tube and compared results with those measured by a photodiode.
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