Feasibility and clinical utility of handheld fundus cameras for retinal imaging

Background/objectives Handheld fundus cameras are portable and cheaper alternatives to table-top counterparts. To date there have been no studies comparing feasibility and clinical utility of handheld fundus cameras to table-top devices. We compare the feasibility and clinical utility of four handheld fundus cameras (Remidio NMFOP, Volk Pictor Plus, Volk iNview, oDocs visoScope) to a table-top camera (Zeiss VisucamNM/FA). Subjects/methods Healthy participants (n = 10, mean age ± SD = 21.0 ± 0.9 years) underwent fundus photography with five fundus cameras to assess success/failure rates of image acquisition. Participants with optic disc abnormalities (n = 8, mean age ± SD = 26.8 ± 15.9) and macular abnormalities (n = 10, mean age ± SD = 71.6 ± 15.4) underwent imaging with the top three scoring fundus cameras. Images were randomised and subsequently validated by ophthalmologists masked to the diagnoses and devices used. Results Image acquisition success rates (100%) were achieved in non-mydriatic and mydriatic settings for Zeiss, Remidio and Pictor, compared with lower success rates for iNview and oDocs. Image quality and gradeability were significantly higher for Zeiss, Remidio and Pictor (p < 0.0001) compared to iNview and oDocs. For cup:disc ratio estimates, similar levels of bias were seen for Zeiss (−0.09 ± SD:0.15), Remidio (−0.07 ± SD:0.14) and Pictor (−0.05 ± SD:0.16). Diagnostic sensitivities were highest for Zeiss (84.9%; 95% CI, 78.2–91.5%) followed by Pictor (78.1%; 95% CI, 66.6–89.5%) and Remidio (77.5%; 95% CI, 65.9–89.0%). Conclusions Remidio and Pictor achieve comparable results to the Zeiss table-top camera. Both devices achieved similar scores in feasibility, image quality, image gradeability and diagnostic sensitivity. This suggests that these devices potentially offer a more cost-effective alternative in certain clinical scenarios.

The Role of Cloud Computing in a Modern Reverse Engineering Workflow at the 5nm Node and Beyond

A modern reverse engineering (RE) workflow contains many challenges, especially as process nodes drop below the 5nm node. With increased complexity, more circuitry is packed into a smaller area, requiring large quantities of raw data collected and subsequently processed to help reconstruct the original schematics. By leveraging inexpensive cloud computing, orders of magnitude improvement in throughput were achieved for 2D image registration and high quality image segmentation was achieved using machine learning.

IMPACT OF AIRPORT SERVICE QUALITY, IMAGE, AND PERCEIVED VALUE ON LOYALTY OF PASSENGERS IN SUVARNABHUMI AIRPORT SERVICE OF THAILAND

Suvarnabhumi Airport is a gateway to Thailand and Asia. It attracts inbound-, outbound- and transit passengers. The objectives of this study were to develop an airport service quality, image and perceived value framework for the loyalty of passengers and to study the direct, indirect and total effects of the factors that influence the loyalty of passengers who used the service at Suvarnabhumi Airport. This quantitative research method uses the questionnaire as a tool for collecting data from 400 passenger samples. According to the Structural Equation Modelling analysis, airport service quality, image and perceived value have had a positive effect on loyalty that airport service quality mainly has an impact on passenger loyalty. There are four latent dimensions of airport service quality, namely, essential services; comfort, convenience and enjoyment; security, customs and passport control; and special facilities, that can help develop loyalty. Perceived value and image on airport administration and management had a significant direct effect to passenger loyalty. Improving these facotrs in order to attract passenger interest and attention can lead to the development of airport organization performance, and to increase competitiveness as an aviation hub in this region.

The Role of Four-Dimensional Automatic Right Ventricular Quantification Technology to Determine RV Function and Hemodynamics in Patients With Pulmonary Hypertension Compared With Right Heart Catheterization

Background: Four-dimensional automatic right ventricular quantification technology (4D auto-RVQ) is a new method that can simultaneously measure right ventricular (RV) structure and strain. The role of 4D auto-RVQ in determining RV function and hemodynamics is not clear. The role of 4D auto-RVQ in determining RV function and hemodynamics is not clear. We assessed the 4D auto-RVQ to measure right heart structure, function, and hemodynamics in patients with pulmonary hypertension (PHTN) correlated with right heart catheterization (RHC).Methods: We enrolled a prospective cohort of 103 patients with PHTN and 25 healthy controls between September 2017 and December 2018. All patients with PHTN underwent echocardiography and RHC. Patients were included if they underwent two-dimensional (2D) and 4D auto-RVQ echocardiographic sequences on the same day as RHC. We analyzed RV functional indices using 2D and 4D auto-RVQ analyses. We divided patients with PHTN into three groups according to echocardiographic image quality as follows: high (n = 24), average (n = 48), and poor (n = 4). Hemodynamic parameters were measured using RHC, including mean right atrial pressure, mean pulmonary arterial pressure, RV cardiac index (RV-CI), and pulmonary vascular resistance.Results: There were significant differences in most 2D and 4D auto-RVQ parameters between patients with PHTN and healthy controls. Interobserver variability showed significant agreement with 4D auto-RVQ for most measurements except for 4D end-diastolic volume. Indices measured by auto 4D-RVQ in the high-quality image group had a good correlation with RHC but not in the average- and poor-quality image group. Mid-RV diameter showed the best predictive power for the right RV-CI [area under the curve (AUC) 0.935; 95% confidence interval (CI), 0.714–0.997; p &lt; 0.001]. RV end-systolic volume &gt;121.50 mL had a 71.43% sensitivity and a 100% specificity to predict right RV-CI (AUC, 0.890; 95% CI, 0.654–0.986; p &lt; 0.001).Conclusions: 4D auto-RVQ may be used to estimate RV function and some hemodynamic changes compared with RHC in PHTN patients with high image quality. Furthermore, a large sample of the study is needed to evaluate RV function by 4D auto-RVQ in PHTN patients with average image quality.

Quantitative Approaches to Study Retinal Neurogenesis

The study of the development of the vertebrate retina can be addressed from several perspectives: from purely qualitative to a more quantitative approach that takes into account its spatiotemporal features, its three dimensional structure and also the regulation and properties at the systems level. Here we review the ongoing transition towards a full four-dimensional characterization of the developing vertebrate retina, focusing on the challenges at the experimental, image acquisition, image processing and quantification. Using the developing zebrafish retina, we illustrate how quantitative data extracted from these type of highly dense three-dimensional tissues depends strongly on the image quality, image processing and algorithms used to segment and quantify. Therefore, we propose that the scientific community that focuses on developmental systems could strongly benefit from a more detailed disclosure of the tools and pipelines used to process and analyze images from biological samples.

A Parallel Partial Enhancement Method for License Plate Localization in Low-Quality Images

Finding an effective license plate localization (LPL) method is challenging owing to different conditions during the image acquisition phase. Most existing methods do not consider various low-quality image conditions that exist in real-world situations. Low-quality image conditions mean that an image can have low resolution, plate imperfection effects, variable illumination environments or background objects similar to the license plate (LP). To improve the anti-interference ability and the speed performance of algorithm, this study aims to develop a parallel partial enhancement method based on color differences that demonstrates improved localization performance for blue–white LP images under low-quality conditions. A novel color difference model is exploited to enhance LP areas and filter non-LP areas. Blue–white color ratio and projection analysis are performed to select the exact LP area from the candidates. Moreover, this study develops a parallel version based on a multicore CPU for real-time processing for industrial applications. An image database including 395 low-quality car images captured from various scenes under different conditions is tested for the performance evaluation. The extensive experiments show the effectiveness and efficiency of the proposed approach.