SignificanceI explore hyperspectral imaging, a rapid and noninvasive technique with significant potential in biometrics and medical diagnosis. Personal identification was performed using cross-sectional hyperspectral images of palms, offering a simpler and more robust method than conventional vascular pattern identification methods.AimI aim to demonstrate the potential of local cross-sectional hyperspectral palm images to identify individuals with high accuracy.ApproachHyperspectral imaging of palms, artificial intelligence (AI)-based region of interest (ROI) detection, feature vector extraction, and dimensionality reduction were utilized to validate personal identification accuracy using the area under the curve (AUC) and equal error rate (EER).ResultsThe feature vectors extracted by the proposed method demonstrated higher intra-cluster similarity when the clustering data were reduced through uniform manifold approximation and projection compared with principal component analysis and t-distributed stochastic neighbor embedding. A maximum AUC of 0.98 and an EER of 0.04% were observed.ConclusionsI proposed a biometric method using cross-sectional hyperspectral imaging of human palms. The procedure includes AI-based ROI detection, feature extraction, dimension reduction, and intra- and inter-subject matching using Euclidean distances as a discriminant function. The proposed method has the potential to identify individuals with high accuracy.
Infrared thermal imaging of brain temperature changes is useful for evaluating cortical activity and disease states, such as stroke. However, the changes depend on a balance between changes in heat generation from metabolism and in heat convection related to blood flow. To discriminate between these effects and gain a clearer understanding of neurovascular metabolic coupling, brain temperature imaging must be improved to measure temperature and blood flow simultaneously. We develop an imaging technique that shows a two-dimensional (2-D) distribution of absolute brain temperature and relative cerebral blood flow changes in anesthetized rats by combining infrared thermal imaging with laser speckle imaging. The changes in brain metabolism and cerebral blood flow are achieved using two different anesthetics (isoflurane and α-chloralose) to evaluate our system. Isoflurane increased cerebral blood flow but decreased metabolism, whereas α-chloralose decreased both parameters. This technique enables simultaneous visualization of brain surface changes in temperature and cerebral blood flow in the same regions. This imaging system will permit further study of neurovascular metabolic coupling in normal and diseased brains.
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