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© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.In recent years, studying the resting-state network (RSN) by using functional near-infrared spectroscopy (fNIRS) has received increased attention. The previous resting-state fNIRS studies mainly adopted the seed-based correlation and the independent component analysis to detect RSN. However, these methods have several inherent problems. For example, the seed-based correlation method relies on seed region selection and neglects the interactions among multiple regions. The ICA method usually relies on manual component selection, which requires rich experience from the experimenter. In the present study, we developed a new approach for fNIRS-RSN detection based on spectral clustering. It consists of two steps. First, it calculates the individual-level partition of the fNIRS measurement region by using spectral clustering with an automatically determined cluster number. Second, the individual-level partitioning results are further clustered. Those clusters with high group consistency are determined as RSN clusters. We validated the method by using simulated data and in vivo fNIRS data. The results showed that the proposed method was effective and robust for fNIRS-RSN detection. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.With recent changes in the legalization of cannabis around the world, there is an urgent need for rapid, yet sensitive, screening devices for testing drivers and employees under the influence of cannabis at the roadside and at the workplace, respectively. Oral fluid lateral flow immunoassays (LFAs) have recently been explored for such applications. While LFAs offer on-site, low-cost and rapid detection of tetrahydrocannabinol (THC), their nominal detection threshold is about 25 ng/ml, which is well above the 1-5 ng/ml per se limits set by regulations. In this paper, we report on the development of a thermo-photonic imaging system that utilizes the commercially available low-cost LFAs but offers detection of THC at unprecedented low concentrations. Our reader technology examines photothermal responses of gold nanoparticles (GNPs) in LFA through lock-in thermography (LIT). Our results (n = 300) suggest that the demodulation of localized surface plasmon resonance responses of GNPs captured by infrared cameras allows for detection of THC concentrations as low as 2 ng/ml with 96% accuracy. Quantification of THC concentration is also achievable with our technology through calibration. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.Blood glucose measurements help to guide insulin therapy, thus reducing disease severities, secondary complications, and related mortalities. Efforts are underway to allow diabetes patients to experience a more convenient way to measure blood glucose and consequently increase their adherence to regular self-monitoring of blood glucose (SMBG). This study demonstrated a new SMBG system that integrated all components of a glucometer via a smartphone's optical sensing module to detect the colorimetric blood strip and obtains the blood glucose concentration with calculations performed by an application install in the smartphone. To validate the accuracy and applicability of the new SMBG system regarding the ISO151972013 accuracy criteria and patient requirements, a clinical trial and usability survey involving participants from different age groups were conducted in collaboration with the China Medical University, where enrolled 120 diabetic patients were asked to operate the new SMBG system to measure their blood glucose concentration, and feedback was obtained from their user experience. The results showed that three different reagent system lots fulfilled the accuracy requirements with values of 97.4-97.5% , and all of the data were within zones A and B of the consensus error grid, which satisfies the ISO 151972013 requirement. The usability survey showed that 97.5% of the participants found the operations convenient, and 100% found the design easy for carrying. This new system could lead to improvements in blood glucose monitoring by people with diabetes, and thus, better management of the disease. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.Pulsed lasers in photoacoustic tomography systems are expensive, which limit their use to a few clinics and small animal labs. We present a method to realize tomographic ultrasound and photoacoustic imaging using a commercial LED-based photoacoustic and ultrasound system. We present two illumination configurations using LED array units and an optimal number of angular views for tomographic reconstruction. The proposed method can be a cost-effective solution for applications demanding tomographic imaging and can be easily integrated into conventional linear array-based ultrasound systems. We present a potential application for finger joint imaging in vivo, which can be used for point-of-care rheumatoid arthritis diagnosis and monitoring. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.We present a dual modality functional optical coherence tomography and photoacoustic microscopy (OCT-PAM) system. The photoacoustic modality employs an akinetic optical sensor with a large imaging window. This imaging window enables direct reflection mode operation, and a seamless integration of optical coherence tomography (OCT) as a second imaging modality. Functional extensions to the OCT-PAM system include Doppler OCT (DOCT) and spectroscopic PAM (sPAM). click here This functional and non-invasive imaging system is applied to image zebrafish larvae, demonstrating its capability to extract both morphological and hemodynamic parameters in vivo in small animals, which are essential and critical in preclinical imaging for physiological, pathophysiological and drug response studies. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.Vascular targeted photodynamic therapy (V-PDT) has been successfully utilized for various vascular-related diseases. To optimize the PDT dose and treatment protocols for clinical treatments and to elucidate the biological mechanisms for V-PDT, blood vessels in the dorsal skin-fold window chamber (DSWC) of nude mice are often chosen to perform in vivo studies. In this study, a new automatic protocol to quantify the vasoconstriction of blood vessels in the DSWC model is proposed, which focused on tracking the pixels of blood vessels in pre- V-PDT images that disappear after V-PDT. The disappearing pixels indicate that the blood vessels were constricted, and thus, the vasoconstriction image for pixel distribution can be constructed. For this, the image of the circular region of interest was automatically extracted using the Hough transform. In addition, the U-Net model is employed to segment the image, and the Speeded-Up Robust Features algorithm to automatically register the segmented pre- and post- V-PDT images.
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