Degraded reality: Using VR/AR to simulate visual impairments

The effects of eye disease cannot be depicted accurately using traditional media. Consequently, public understanding of eye disease is often poor. We present a VR/AR system for simulating common visual impairments, including disability glare, spatial distortions (Metamorphopsia), the selective blurring and filling-in of information across the visual field, and color vision deficits. Unlike most existing simulators, the simulations are informed by patients' self-reported symptoms, can be quantitatively manipulated to provide custom disease profiles, and support gaze-contingent presentation (i.e., when using a VR/AR headset that contains eye-tracking technology, such as the Fove0). Such a simulator could be used as a teaching/empathy aid, or as a tool for evaluating the accessibility of new products and environments

Testing a phantom eye under various signal-to-noise ratio conditions using eleven different OCT devices

We compared eleven OCT devices in their ability to quantify retinal layer thicknesses under different signal-strength conditions, using a commercially available phantom eye. We analyzed a medium-intensity 50 µm layer in an identical manner for all devices, using the provided log-scale images and a reconstructed linear-scale tissue reflectivity metric. Thickness measurements were highly comparable when the data were analyzed in an identical manner. With optimal signal strength, the thickness of the 50 µm layer was overestimated by a mean of 4.3 µm in the log-scale images and of 2.7 µm in the linear-scale images

Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning

Purpose: To assess the performance of a perimetric strategy using structure–function predictions from a deep learning (DL) model. Methods: Visual field test–retest data from 146 eyes (75 patients) with glaucoma with (median [5th–95th percentile]) 10 [7, 10] tests per eye were used. Structure–function predictions were generated with a previously described DL model using cicumpapillary optical coherence tomography (OCT) scans. Structurally informed prior distributions were built grouping the observed measured sensitivities for each predicted value and recalculated for each subject with a leave-one-out approach. A zippy estimation by sequential testing (ZEST) strategy was used for the simulations (1000 per eye). Groundtruth sensitivities for each eye were the medians of the test–retest values. Two variations of ZEST were compared in terms of speed (average total number of presentations [NP] per eye) and accuracy (average mean absolute error [MAE] per eye), using either a combination of normal and abnormal thresholds (ZEST) or the calculated structural distributions (S-ZEST) as prior information. Two additional versions of these strategies employing spatial correlations were tested. Results: S-ZEST was significantly faster, with a mean average NP of 213.87 (SD = 28.18), than ZEST, with a mean average NP of 255.65 (SD = 50.27) (P < 0.001). The average MAE was smaller for S-ZEST (1.98; SD = 2.37) than ZEST (2.43; SD = 2.69) (P < 0.001). Spatial correlations further improved both strategies (P < 0.001), but the differences between ZEST and S-ZEST remained significant (P < 0.001). Conclusions: DL structure–function predictions can significantly improve perimetric tests. Translational Relevance: DL structure–function predictions from clinically available OCT scans can improve perimetry in glaucoma patients

Sustainability index for agribusiness products considering territorial bases and life cycle thinking.

The sustainability index (SI) development for agricultural products was a Brazilian Agricultural, Livestock and Provisioning Ministry, (MAPA) demand. This work seeks by participative process, to define sustainability principles, criteria and agricultural products patterns. Theses principles have universal characters liable to expand its application to several agribusiness links by future criteria in the several territorial contexts through out the patterns to be defined to each biome monitored by satellites. The SI must have credibility and international recognition. Among their principles are: Conformity with the agreement, treaties and international conventions; Conformity with the national legislation; Localization; Integration; Monitoring and continuous improvement. The participative elaboration of the sustainability principles with the more representative agribusiness sectors, science and technology areas and the public and private institutions is allowing delineating the environment conduct, innovation and business for a future guiding to criteria formatting of the and SI patterns

Geotraceability and life cycle assessment in environmental life cycle management: towards sustainability.

Sustainability is an emerging concept in product chains and integrates environmental, social, and economic aspects during the product's life cycle. Recently, the demand for environmental quality has required information about the products' life cycle. Life Cycle Assessment (LCA) includes the inventory analysis, where the products´life cycle are systematized, and the Life Cycle Impact Assessment, when the environmental impacts potentials are calculated. A powerful tool to describe the history, use, and lication of a product in called geotraceability..

Spatiotemporal summation of perimetric stimuli in healthy observers

Spatial summation of perimetric stimuli has been used to derive conclusions about the spatial extent of retinal-cortical convergence, mostly from the size of the critical area of summation (Ricco's area, RA) and critical number of retinal ganglion cells (RGCs). However, spatial summation is known to change dynamically with stimulus duration. Conversely, temporal summation and critical duration also vary with stimulus size. Such an important and often neglected spatiotemporal interaction has important implications for modeling perimetric sensitivity in healthy observers and for formulating hypotheses for changes measured in disease. In this work, we performed experiments on visually heathy observers confirming the interaction of stimulus size and duration in determining summation responses in photopic conditions. We then propose a simplified computational model that captures these aspects of perimetric sensitivity by modelling the total retinal input, the combined effect of stimulus size, duration, and retinal cones-to-RGC ratio. We additionally show that, in the macula, the enlargement of RA with eccentricity might not correspond to a constant critical number of RGCs, as often reported, but to a constant critical total retinal input. We finally compare our results with previous literature and show possible implications for modeling disease, especially glaucoma

Revisiting the Drasdo Model: Implications for Structure-Function Analysis of the Macular Region

Purpose: To provide a consistent implementation of a retinal ganglion cell (RGC) displacement model proposed by Drasdo et al. for macular structure-function analysis, customizable by axial length (AL). Methods: The effect of axial length on the shape of the inner retina was measured on 235 optical coherence tomography (OCT) scans from healthy eyes, to provide evidence for geometric scaling of structures with eye size. Following this assumption, we applied the Drasdo model to map perimetric stimuli on the radially displaced RGCs using two different methods: Method 1 only displaced the center of the stimuli; Method 2 applied the displacement to every point on the edge of the stimuli. We compared the accuracy of the two methods by calculating, for each stimulus, the number of expected RGC receptive fields and the number RGCs calculated from the histology map, expected to be equivalent. The same calculation was repeated on RGC density maps derived from 28 OCT scans from 28 young healthy subjects (age < 40 years) to confirm our results on clinically available measurements. Results: The size of the retinal structures significantly increased with AL (P < 0.001) and was well predicted by geometric scaling. Method 1 systematically underestimated the RGC counts by as much as 60%. No bias was observed with Method 2. Conclusions: The Drasdo model can effectively account for AL assuming geometric scaling. Method 2 should be used for structure-function analyses. Translational Relevance: We developed a free web App in Shiny R to make our results available for researchers