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Abstract:The retinal pigment epithelial (RPE) cells contain intrinsic fluorophores that can be visualized using infrared autofluorescence (IRAF). Although IRAF is routinely utilized in the clinic for visualizing retinal health and disease, currently, it is not possible to discern cellular details using IRAF due to limits in resolution. We demonstrate that the combination of adaptive optics (AO) with IRAF (AO-IRAF) enables higher-resolution imaging of the IRAF signal, revealing the RPE mosaic in the living human eye. Quantitative analysis of visualized RPE cells in 10 healthy subjects across various eccentricities demonstrates the possibility for in vivo density measurements of RPE cells, which range from 6505 to 5388 cells/mm 2 for the areas measured (peaking at the fovea). We also identified cone photoreceptors in relation to underlying RPE cells, and found that RPE cells support on average up to 18.74 cone photoreceptors in the fovea down to an average of 1.03 cone photoreceptors per RPE cell at an eccentricity of 6 mm. Clinical application of AO-IRAF to a patient with retinitis pigmentosa illustrates the potential for AO-IRAF imaging to become a valuable complementary approach to the current landscape of high resolution imaging modalities. References and links1. U. Kellner, S. Kellner, and S. Weinitz, "Fundus autofluorescence (488 nm) and near-infrared autofluorescence (787 nm) visualize different retinal pigment epithelium alterations in patients with age-related macular degeneration," Retina 30(1), 6-15 (2010). 2.

Abstract. In Korea, telematics is regarded as the technology to enhance and make everyday-driving experience more comfortable and safer. An essential part of the telematics is navigation and it is mainly based on GPS as the choice of positioning technology. The accuracy of GPS, however, is approximately ten to twenty meters. Combining with map-matching technologies, most navigation systems guide drivers with a best effort manner. In addition to telematics, RFID (Radio Frequency Identification) is an old but newly emerged technology. In this paper, we incorporate RFID technology into a navigation system to improve the accuracy. The skeleton of the idea is as follows: install RFID tags on roads in a certain way, store very accurate location information along with other necessary information in the tags, add an RFID reader module to the navigation system, and use this new location information along with GPS and a gyroscope to produce highly accurate location information. With this scheme, the accuracy of positioning can be dramatically improved, especially in tunnels and in downtown areas. Preliminary results show that this idea is feasible.

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PurposeAdaptive optics scanning light ophthalmoscopy (AOSLO) has enabled quantification of the photoreceptor mosaic in the living human eye using metrics such as cell density and average spacing. These rely on the identification of individual cells. Here, we demonstrate a novel approach for computer-aided identification of cone photoreceptors on nonconfocal split detection AOSLO images.MethodsAlgorithms for identification of cone photoreceptors were developed, based on multiscale circular voting (MSCV) in combination with a priori knowledge that split detection images resemble Nomarski differential interference contrast images, in which dark and bright regions are present on the two sides of each cell. The proposed algorithm locates dark and bright region pairs, iteratively refining the identification across multiple scales. Identification accuracy was assessed in data from 10 subjects by comparing automated identifications with manual labeling, followed by computation of density and spacing metrics for comparison to histology and published data.ResultsThere was good agreement between manual and automated cone identifications with overall recall, precision, and F1 score of 92.9%, 90.8%, and 91.8%, respectively. On average, computed density and spacing values using automated identification were within 10.7% and 11.2% of the expected histology values across eccentricities ranging from 0.5 to 6.2 mm. There was no statistically significant difference between MSCV-based and histology-based density measurements (P = 0.96, Kolmogorov-Smirnov 2-sample test).ConclusionsMSCV can accurately detect cone photoreceptors on split detection images across a range of eccentricities, enabling quick, objective estimation of photoreceptor mosaic metrics, which will be important for future clinical trials utilizing adaptive optics.

Visualizing the cellular manifestation of disease has recently been aided by an increasing number of adaptive optics (AO)-based imaging modalities developed for the living human eye. However, simultaneous visualization of multiple, interacting cell types within a complete neural–epithelial–vascular complex has proven challenging. By incorporating AO with indocyanine green angiography, we demonstrate the possibility of imaging photoreceptors, retinal pigment epithelial cells, and choriocapillaris in the living human eye. Unexpectedly, we found that there was uptake of indocyanine green dye into the retinal pigment epithelial cells in the earliest phases of imaging, which formed the basis for devising a strategy to visualize the choriocapillaris. Our results expand the range of applications for an existing, FDA-approved, systemically injected fluorescent dye. The combined multimodal approach can be used to evaluate the complete outer retinal complex at the cellular level, a transformative step toward revealing the in vivo cellular status of neurodegenerative conditions and blinding diseases.

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