Fig. 1 Demonstration of OCT scan registration in different subjects. (A) Lateral registration was achieved by foveal center alignment in a 9×9-mm image, with the nasal side flipped in the left eyes to match with the right eyes. (B) Axial registration is achieved by axially normalizing the A-lines according to percent retinal depth.
Fig. 2 Demonstration of 3-D detection of nonperfusion. The perfusion volume simulated by convoluting the angiogram volume with 3-D Gaussian kernel, and then compared between reference and diseased retinas using Eq. (2) to calculate the 3-D nonperfusion map. The 3-D nonperfusion map is color-coded by percent retinal depth (ILM: 0, BM: 100).
Fig. 3 Diagnostic power of various pathology indexes to differentiate non-referable DR from referable DR subjects. The pathology index for each clinical feature was calculated as the decibel ratio of the averaged deviation magnitude from a target retinal scan (Pd) to baselines (Ph) from healthy subjects. (A) The combined pathology index achieved an R=0.95 Spearman correlation coefficient with the DR severity. The black dotted line indicates a pathology index cut-off PI=6 corresponding to the best diagnostic point in B. (B) Receiver operating characteristic curves for the pathology indexes of each clinical feature, and the combined one for referable vs. non-referable DR classification. The optimal operating point of the ROC curve for the averaged PI was determined as 1-specificity= 0.28 and sensitivity=0.87, output from the parameter OPTROCPT of the MATLAB function perfcurve( ).
Fig. 1 Representative capillary sO2 along with that in major vessels (A: artery, V: vein) in one rat retina responding to regulation in oxygen concentration in inhaled gas, from 21% (normoxia) to 15% (hypoxia), then to 100% (hyperoxia) and to 21% (return to normoxia). The angiogram (2×2-mm) was obtained by averaging all 8 scans at all conditions acquired in the same region. The sO2 in capillary segments corresponded to trends shown by the sO2 in major vessels, which decreased with the reduction of oxygen concentration in the inhaled gas.
Fig. 2 Ultra-wide-field angiogram of rat retinal vessels stitched from multiple scans with smaller field of view.
Fig. 1 En face images (2.2 × 2.2 mm2) showing retinal vascular perfusion responses to acute IOP elevation
Comprehensive retinal responses to acute IOP elevation
which include retinal oxygen extraction and oxygen metabolism, as well as structural reflectivity, angiography and blood flow, all provided with vis-OCT simultaneously.
Fig. 2 Demonstration of phase unwrapping of a vein and an artery affected by phase wrapping, as well as a vein free of phase wrapping.
Fig. 1 The 3D schematic vascular network illustrates the flow transition from artery to vein in rat retina with microvasculature architecture corresponding to the current findings.
Fig. 2 Retinal oxygen metabolic rate measurement with visible light OCT.
rTRO2: Retinal oxygen transport rate.
rMRO2: Retinal oxygen metabolic rate.
Fig. 1 Logarithmic absorption extinction coefficients of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (Hb) in the wavelength range from 400 nm to 1000 nm. The much higher extinction coefficients in the visible range (vis-OCT) compared to the infrared range (standard OCT) provides a better contrast to quantify oxygen saturation (sO2).
Oxygen saturation is the fraction of oxygen-saturated hemoglobin relative to total hemoglobin in the blood. If quantified accurately, sO2 could be used as a biomarker to monitor retinal metabolism and provide a valuable early indicator of ocular disease.
Fig. 2 (a)-(c): Arteries demonstrate higher oxygen saturation (sO2) than veins by visible light OCT oximetry. Red: artery. Green: vein. The sO2 of each vessel is overlaid on structural en face images. (d)- (f): Fundus images. (g)- (i): Doppler OCT images around the optic disc show opposite flow directions between arteries and veins.
Fig. 1 (A) Schematic of the visible light optical coherence tomography (vis-OCT) system for rat retina imaging. L1, L2: Lens. (B) Calibrated spectrum in spectrometer using a Neon calibration light source. The center wavelength is 560 nm and full maximum at half width (FWHM) bandwidth is 90 nm. (C) Maximum sensitivity was 89 dB considering the light passes a neutral density (ND) filter (OD = 3.0) twice. Inset shows the measured axial resolution 1.7 μm in air, which is equivalent to 1.2 μm in tissue.
Fig. 2 3.2 × 3.2-mm rat retinal en face angiograms of the (A) superficial vascular plexus (SVP), (B) intermediate capillary plexus (ICP), (C) deep capillary plexus (DCP), and (D) choriocapillaris (CC). scale bar = 200 μm.
I designed a novel nano-structure which can launch surface plasmon resonance (SPR) modes efficiently from the back side of metal film, can excite the SPR under the normal incident light, demonstrated very narrow (~4 nm) resonance line width, and showed ultra-wide spectral tunability.
I assisted to develop an intrusion classification algorithm based on wavelet packet transform, Shannon entropy and neural network.
I developed a Sagnac-based optical fiber sensing system and a "twice-FFT" algorithm to detect and localize vibrational intrusions along a pipeline in real-time.
Thin Film Transistor (TFT)
I fabricated the IZO: W TFT with magnetron sputtering at different oxygen partial pressure, and measured its electric and optical characterization with step profiler, SEM and spectrophotometer.