05). Significant linear correlations were found between MG tortuosity and the lid margin score, meiboscore, meibum expressibility score, and TBUT ( 0.05). When the diagnosis of obstructive MGD was based on the tortuosity of the central eight MGs of both eyelids, the sensitivity and specificity were 100% and 100%, respectively. MG tortuosity is an effective index to delineate MG morphology and to diagnose MGD, especially for the diagnosis of early-stage MGD. Calculating tortuosity quantitatively may play an important role in the diagnosis of MGD. Calculating tortuosity quantitatively may play an important role in the diagnosis of MGD. Using a geometrically derived model and a virtual curb simulator, we quantify the degree to which a wearable device that projects a laser line onto tripping hazards in a pedestrian's path improves visual recognition for people with visual impairments (VI). We confirm this with subjects' performance on computer simulations of low contrast curbs. We derive geometric expressions quantifying the visual cue users perceive when a single laser line is projected from their hip onto a curb. We show how the efficacy of this cue changes with the angle of the laser line relative to the subject's walking trajectory. We confirm this result with data from three subjects with VI in a simulated curb recognition task in which subjects classified computer images as an "Ascending," "Flat," or "Descending" curb. The derived model predicts that human recognition performance depends strongly on the laser line angle and the subject data confirms this ( = 0.86 < 0.001). The laser line cue improved subject accuracy from a chance level of 33% to 95% for a simulated, one-inch, low-contrast curb at a distance of five feet. Recognition of curbs in low light can be improved by augmenting the scene with a single laser line projected from a user's hip, if the angle of laser line is appropriately selected. A majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. https://www.selleckchem.com/products/apx2009.html Enhancing residual vision could promote safety, increase independence, and reduce medical costs. A majority of people with VI rely on their impaired residual vision for mobility, rather than a mobility aid, resulting in increased injury for this population. Enhancing residual vision could promote safety, increase independence, and reduce medical costs. To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty. We analyzed 383 post ultrathin Descemet stripping automated endothelial keratoplasty images from 41 eyes acquired with a Topcon SP-1P specular microscope at 1, 3, 6, and 12 months after surgery. The estimated parameters were endothelial cell density (ECD), coefficient of variation (CV), and hexagonality (HEX). Manual segmentation was performed in all images. Our method provided an estimate for ECD, CV, and HEX in 98.4% of the images, whereas Topcon's software had a success rate of 71.5% for ECD/CV and 30.5% for HEX. For the images with estimates, the percentage error in our method was 2.5% for ECD, 5.7% for CV, and 5.7% for HEX, whereas Topcon's software provided an error of 7.5% for ECD, 17.5% for CV, and 18.3% for HEX. Our method was significantly better than Topcon's ( < 0.0001) and was not statistically significantly different from the manual assessments ( > 0.05). At month 12, the subjects presented an average ECD = 1377 ± 483 [cells/mm ], CV = 26.1 ± 5.7 [%], and HEX = 58.1 ± 7.1 [%]. The proposed method obtains reliable and accurate estimations even in challenging specular images of pathologic corneas. CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use. CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use. We developed a method to automatically locate and quantify graft detachment after Descemet's membrane endothelial keratoplasty (DMEK) in anterior segment optical coherence tomography (AS-OCT) scans. A total of 1280 AS-OCT B-scans were annotated by a DMEK expert. Using the annotations, a deep learning pipeline was developed to localize scleral spur, center the AS-OCT B-scans and segment the detached graft sections. Detachment segmentation model performance was evaluated per B-scan by comparing (1) length of detachment and (2) horizontal projection of the detached sections with the expert annotations. Horizontal projections were used to construct graft detachment maps. All final evaluations were done on a test set that was set apart during training of the models. A second DMEK expert annotated the test set to determine interrater performance. Mean scleral spur localization error was 0.155 mm, whereas the interrater difference was 0.090 mm. The estimated graft detachment lengths were in 69% of the cases within a 10-pixel (∼150 µm) difference from the ground truth (77% for the second DMEK expert). Dice scores for the horizontal projections of all B-scans with detachments were 0.896 and 0.880 for our model and the second DMEK expert, respectively. Our deep learning model can be used to automatically and instantly localize graft detachment in AS-OCT B-scans. Horizontal detachment projections can be determined with the same accuracy as a human DMEK expert, allowing for the construction of accurate graft detachment maps. Automated localization and quantification of graft detachment can support DMEK research and standardize clinical decision-making. Automated localization and quantification of graft detachment can support DMEK research and standardize clinical decision-making.The purpose of the present study is to explore the psychometric properties of the U.S. Army's Family Global Assessment Tool (GAT), which assesses the psychosocial fitness of Army families. With data from 1,692 Army spouses, we examined the structure, reliability and validity of the GAT, using confirmatory factor analysis (CFA) and two validity studies. Fifty-three items and 9 factors were retained following CFA. This model provided a good fit, and scales demonstrated strong internal consistency. Bivariate correlations and results from a theoretically driven model provide preliminary evidence of validity. Findings support the usefulness of the GAT for measuring psychosocial fitness of Army spouses.