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Abstract To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P

Abstract Purpose To evaluate the association of body stature with ocular biometrics and refraction in preschool children. Methods A cross-sectional, school-based study was conducted in Shenzhen, China. Preschool children aged 3 to 6 from 10 randomly-selected kindergartens were recruited. Ocular biometric parameters, including axial length (AL), anterior chamber depth (ACD), vitreous chamber depth (VCD), corneal radius curvature (CR), axial length to corneal radius ratio (AL-to-CR ratio) and lens thickness (LT) were measured using non-contact partial-coherence laser interferometry. Cycloplegic refractions were obtained by a desktop autorefractor. Body height and weight were measured using standard procedures. The association between body stature and ocular biometrics were analyzed with univariable and multivariable regression model. Results A total of 373 preschoolers were included. AL, ACD, VCD, CR, and AL-to-CR ratio, were positively associated with height and weight (p

Abstract The interactions between white-to-white corneal diameter (WTW) and other ocular biometrics are important for planning of refractive surgery and understanding of ocular structural changes in myopia, but such interactions are rarely investigated in young myopic adults. This is a retrospective study involving 7893 young myopic adults from five centers. WTW and other ocular biometrics were measured by Pentacam. The ocular biometrics included anterior corneal curvature (AK) and posterior corneal curvature (PK), central corneal thickness (CCT) and corneal volume (CV), anterior and corneal eccentricity and asphericity, anterior corneal astigmatism (ACA) and posterior corneal astigmatism, anterior chamber depth (ACD), and anterior chamber volume (ACV). The ocular biometrics were compared among eyes of different WTW quartiles. Multivariate linear regression was used to assess the linear associations between WTW and other ocular biometrics adjusting for age, gender and spherical equivalent. In eyes of different WTW quartiles, other ocular biometrics were also significantly different (all P

Tong Bao,1,&ast; Liru Qin,2,&ast; Guimei Hou,1 Hongmei Jiang,1 Lifeng Wang,1 Ying Wang,1 Junhui Wu,1 Jinli Wang,3 Yunlei Pang4 1Department of Ophthalmological Examination, Chifeng Chaoju Eye Hospital, Chifeng, People’s Republic of China; 2Department of Ophthalmology, Inner Mongolia Baogang Hospital, Baotou, People’s Republic of China; 3Department of Cataract, Chifeng Chaoju Eye Hospital, Chifeng, People’s Republic of China; 4Department of Ophthalmic Plastic Surgery, Chifeng Chaoju Eye Hospital, Chifeng, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jinli Wang, Department of Cataract, Chifeng Chaoju Eye Hospital, Chifeng, People’s Republic of China, Email chaojueyewjl66@163.com Yunlei Pang, Department of Ophthalmic Plastic Surgery, Chifeng Chaoju Eye Hospital, Chifeng, People’s Republic of China, Email 29483645@qq.comObjective: To investigate the association between the peripheral refractive errors of the fundus in different regions and moderate and high myopia.Methods: In this case-control study, 320 children and adolescents aged 6 to 18 years were recruited. Peripheral refractive errors were measured using multispectral retinal refractive topography (MRT). Spherical equivalent (SE) and cylinder errors were classified into low, moderate, and high categories based on the magnitude range. Logistic regression was performed to test the factors associated with myopia.Results: There were 152 participants with low myopia and 168 participants with moderate and high myopia included in the current study. Participants with moderate and high myopia were most likely to be older, with larger axial length (AL), lower SE, less time to watch electronic devices on the weekend, a higher difference between central refractive error and paracentral refractive error from the superior side of the retina (RDV-S), but a smaller difference between the central refractive error and paracentral refractive error from the inferior side of the retina (RDV-I) than those with low myopia (all P < 0.05). After logistic analysis, female sex (odds ratio [OR] = 4.14; 95% confidence interval [CI] = 2.16– 7.97, P < 0.001), AL (OR = 6.88, 95% CI = 4.33– 10.93, P < 0.001), and RDV-I (OR = 0.52, 95% CI = 0.32– 0.86, P = 0.010) were independent factors for moderate and high myopia.Conclusion: Our study demonstrated that the retina peripheral refraction of the eyes (RDV-I) was associated with moderate and high myopia, and RDV-S was only associated with high myopia.Keywords: peripheral refractive errors, myopia, spherical equivalent, logistic analysis, ocular biometrics

To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P < 0.05). Eyes in higher CC quartiles had lower WTW, thinner CCT, lower CV at 3 mm and 5 mm, lower ACD, and lower ACV (all P < 0.001), but had larger ACA, larger PCA, less PCE and less PCAP (all P < 0.001), compared to eyes in lower CC quartiles. The trends of CV at 7 mm, ACE and ACAP were inconsistent in different CC quartiles. After adjusting for age, gender and spherical equivalent with multivariate linear regression, CC was positively correlated to CV at 7 mm (βs = 0.069), ACA (βs = 0.194), PCA (βs = 0.187), ACE (βs = 0.072), PCAP (βs = 0.087), and ACD (βs = 0.027) (all P < 0.05), but was negatively correlated to WTW (βs = − 0.432), CCT (βs = − 0.087), CV-3 mm (βs = − 0.066), ACAP (βs = − 0.043), PCE (βs = − 0.062), and ACV (βs = − 0.188) (all P < 0.05). CC was associated with most of the other anterior segment biometrics in young myopic adults. These associations are important for better understanding of the interactions between different anterior segment structures in young myopic patients, and are also useful for the exploration of the pathogenesis of myopia. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the association of body stature with ocular biometrics and refraction in preschool children. Methods: A cross-sectional, school-based study was conducted in Shenzhen, China. Preschool children aged 3 to 6 from 10 randomly-selected kindergartens were recruited. Ocular biometric parameters, including axial length (AL), anterior chamber depth (ACD), vitreous chamber depth (VCD), corneal radius curvature (CR), axial length to corneal radius ratio (AL-to-CR ratio) and lens thickness (LT) were measured using non-contact partial-coherence laser interferometry. Cycloplegic refractions were obtained by a desktop autorefractor. Body height and weight were measured using standard procedures. The association between body stature and ocular biometrics were analyzed with univariable and multivariable regression model. Results: A total of 373 preschoolers were included. AL, ACD, VCD, CR, and AL-to-CR ratio, were positively associated with height and weight (p < 0.05), whereas LT was negatively associated with height and weight (p < 0.01). No association was observed between stature and central cornea thickness and refraction. After adjusted for age and gender in a multivariable regression model, AL had positive associations with height (p < 0.01) and weight (p < 0.01). However, refraction had no significant association with stature parameters. Conclusion: Taller and heavier preschoolers had eyes with longer AL, deeper vitreous chamber, and flatter cornea. The significant associations between body stature and ocular biometric parameters reveal the driving influence of body development on the growth of eyeballs in preschoolers. [ABSTRACT FROM AUTHOR]

The interactions between white-to-white corneal diameter (WTW) and other ocular biometrics are important for planning of refractive surgery and understanding of ocular structural changes in myopia, but such interactions are rarely investigated in young myopic adults. This is a retrospective study involving 7893 young myopic adults from five centers. WTW and other ocular biometrics were measured by Pentacam. The ocular biometrics included anterior corneal curvature (AK) and posterior corneal curvature (PK), central corneal thickness (CCT) and corneal volume (CV), anterior and corneal eccentricity and asphericity, anterior corneal astigmatism (ACA) and posterior corneal astigmatism, anterior chamber depth (ACD), and anterior chamber volume (ACV). The ocular biometrics were compared among eyes of different WTW quartiles. Multivariate linear regression was used to assess the linear associations between WTW and other ocular biometrics adjusting for age, gender and spherical equivalent. In eyes of different WTW quartiles, other ocular biometrics were also significantly different (all P < 0.05). After adjusting for age, gender and spherical equivalent, WTW was positively correlated to AK (β = 0.26 to 0.29), ACA (β = 0.13), anterior corneal asphericity (β = 0.05), PK (β = 0.33 to 0.34), posterior corneal asphericity (β = 0.13), ACD (β = 0.29), and ACV (β = 40.69), and was negatively correlated to CCT (β = − 6.83), CV (β = − 0.06 to − 0.78), anterior corneal eccentricity (β = − 0.035), and posterior corneal eccentricity (β = − 0.14) (all P < 0.001). In conclusion, we found that in young myopic adults, larger WTW was associated with thinner corneal thickness, flatter corneal curvature, more anterior corneal toricity, less corneal eccentricity and asphericity, and broader anterior chamber. Our findings may fill in the gap of literature, and help us better understand how the anterior segment structures interact with the WTW in myopia. [ABSTRACT FROM AUTHOR]

The sclera has recently been gaining attention as a biometric modality due to its various desirable characteristics. A key step in any type of ocular biometric recognition, including sclera recognition, is the segmentation of the relevant part(s) of the eye. However, the high computational complexity of the (deep) segmentation models used in this task can limit their applicability on resource-constrained devices such as smartphones or head-mounted displays. As these devices are a common desired target for such biometric systems, lightweight solutions for ocular segmentation are critically needed. To address this issue, this paper introduces IPAD (Iterative Pruning with Activation Deviation), a novel method for developing lightweight convolutional networks, that is based on model pruning. IPAD uses a novel filter-activation-based criterion (ADC) to determine low-importance filters and employs an iterative model pruning procedure to derive the final lightweight model. To evaluate the proposed pruning procedure, we conduct extensive experiments with two diverse segmentation models, over four publicly available datasets (SBVPI, SLD, SMD and MOBIUS), in four distinct problem configurations and in comparison to state-of-the-art methods from the literature. The results of the experiments show that the proposed filter-importance criterion outperforms the standard L1 and L2 approaches from the literature. Furthermore, the results also suggest that: (i) the pruned models are able to retain (or even improve on) the performance of the unpruned originals, as long as they are not over-pruned, with RITnet and U-Net at 50% of their original FLOPs reaching up to 4% and 7% higher IoU values than their unpruned versions, respectively, (ii) smaller models require more careful pruning, as the pruning process can hurt the model’s generalization capabilities, and (iii) the novel criterion most convincingly outperforms the classic approaches when sufficient training data is available, implying that the abundance of data leads to more robust activation-based importance computation.

With the unprecedented mobile technology revolution, mobile devices have transcended from being the primary means of communication to an all-in-one platform. Consequently, an increasing number of individuals are accessing online services for e-commerce and banking via smartphones instead of traditional desktop computers. However, smartphones can be easily misplaced, lost, or stolen more often than other computing devices, thereby demanding effective user authentication mechanisms for device unlocking and secured transactions. Ocular biometrics has obtained significant attention from academia and industry because of its accuracy, security, and ease of use in mobile devices. Several studies have demonstrated the efficacy of deep learning models for ocular-based user authentication on smartphones. However, these high-performing models require enormous space and computational complexity due to the millions of parameters and computations involved. These requirements make their deployment on resource-constrained smartphones challenging. To this end, a handful of studies have been proposed for compact-size ocular-based deep-learning models to facilitate on-device deployment. In this paper, we conduct a thorough analysis of the existing neural network compression techniques applied as a standalone and in combination for ocular-based user authentication. Extensive experimental validation is performed on the two latest large-scale ocular biometric datasets collected using smartphones, namely, UFPR and VISOB 2.0 datasets. This study benchmarks the results of advanced compression techniques for further research and development in lightweight models for ocular-based user authentication on smartphones.

This study aimed to investigate changes in non-cycloplegic ocular biometrics during the initial six months of treatment with a 0.1% atropine loading dose and 0.01% atropine compared with a placebo and analyze their contribution to the treatment effect on cycloplegic spherical equivalent (SE) progression. The study was based on a randomized, double-masked, placebo-controlled, multicenter trial evaluating a 0.1% atropine six-month loading dose and 0.01% atropine in reducing myopic progression in Danish children. The treatment phase was 24 months, and the washout phase was 12 months. Parameters measured included changes in axial length (AL), anterior chamber depth (ACD), lens thickness (LT), vitreous chamber depth (VCD), and choroidal thickness (ChT), while cycloplegic SE and lens power were calculated. Longitudinal changes and contributions to treatment effects were analyzed using constrained linear mixed models and mediation analyses, respectively. After six months, AL was 0.13 mm shorter (95% confidence interval [CI], −0.18 to −0.07 [adjusted p < 0.001]) and 0.06 mm shorter (95% CI, −0.11 to −0.01 [adjusted p = 0.060]) with a 0.1% atropine loading dose and 0.01% atropine, respectively, compared to the placebo group. Similar concentration-dependent changes were found with ACD, LT, VCD, ChT, and cycloplegic SE. Although the treatment effects trended toward concentration-dependent responses, only the treatment effect mediated by AL at three months differed significantly between 0.01% atropine and a 0.1% atropine loading dose (adjusted p = 0.023). Several ocular biometrics, including AL, ACD, and LT, changed dose-dependently during low-dose atropine treatment. Moreover, the treatment effect of atropine on SE progression was mediated by a subset of ocular biometrics, mainly AL, with trends toward concentration dependency and distributional shifts over time. [ABSTRACT FROM AUTHOR]

Abstract Corneal volume (CV) is a useful index for detecting forme fruste keratoconus from normal corneas. It can be used to evaluate the whole cornea, since it can measure corneal areas up to 10 mm in diameter. Thus, CV has become the clinicians' interest as a diagnostic tool of corneal ectatic disease and a measure of corneal integrity to determine suitability for refractive surgery. We conducted a cross‐sectional study including 7893 myopic patients from five ophthalmic centers to investigate the distribution pattern of CV. Our study showed that distribution of CV‐3, CV‐5, and CV‐7 mm were slightly positively skewed and the 2.5th to 97.5th percentiles were 3.6–4.4, 10.4–12.8, 22.5–27.5 mm3, respectively. Central corneal thickness (CCT) was significantly correlated with CV in all measurement regions. The correlation between CV and CCT showed an inconsistent trend with the increase of age. The correlation coefficient between CV and CCT did not change significantly with the increase of myopia degree in low to moderate myopia, but fluctuated significantly in high myopia (less than −6.0 diopters). According to our results, corneal volume follows a slightly positively skewed distribution pattern in myopic Chinese patients. The information is useful for screening refractive surgery candidates and assessing the risk of corneal refractive surgery.

Abstract Purpose To investigate the prevalence of myopia in Chinese primary school students and their ocular biometrics including axial length (AL), corneal radius of curvature (CRC) and spherical equivalent refraction (SER). To analyze their association with potential myopia risk factors, such as body mass index (BMI), cram school, time of outdoor activity and electronic screen use. Methods In this cross-sectional study of 4500 primary school students from 5 schools, participants underwent refraction using non-cycloplegic autorefractor and visual acuity testing. A follow-up study in the same schools was conducted in 2022. Myopia was defined as SER ≤ -0.50 diopter (D) and uncorrected visual acuity (UCVA)

Purpose: To investigate the characteristics of eyes with large variations in predicted refraction using four traditional intraocular lens (IOL) formulas and evaluate the accuracy of new-generation intraocular lens power calculation formulas. Methods: Eyes that had variation in predicted refraction (≥ 0.75 D) using four traditional formulas (SRK/T, Holladay 1, Hoffer Q, and Haigis formulas) were included. Axial length (AL), anterior chamber depth (ACD), average keratometry (AK), and the ratio of axial length to corneal radius (AL/CR) were measured. New-generation formulas (Barrett Universal II, Emmetropia Verifying Optical 2.0, Kane, and Pearl-DGS formulas) and traditional formulas were compared. The median absolute error (MedAE) was the main parameter to evaluate the accuracy of formulas. Results: A total of 79 participants (79 eyes) who had variation in predicted refraction of (≥ 0.75 D) using four traditional formulas out of 510 eyes (510 patients) underwent uncomplicated cataract surgeries. The Barrett Universal II (0.29 D), EVO 2.0 (0.31 D), Kane (0.30 D), and Pearl-DGS (0.33 D) formulas produced significantly lower median absolute errors (MedAEs) than the Hoffer Q (0.61 D) and Holladay 1 (0.59 D) formulas (P < 0.01). The Wang-Koch (WK) adjustment significantly improved the accuracy of the Holladay 1 formula in long eyes (P < 0.001). Conclusions: Abnormal AL, ACD, and AK are more likely to lead to prediction errors using traditional formulas. New-generation formulas and traditional formulas with WK adjustment showed satisfactory prediction accuracy. [ABSTRACT FROM AUTHOR]

BackgroundSeveral studies have shown that various concentrations of low-concentration atropine can reduce myopia progression and control axial elongation safely and efficiently in children. The aim of this study was to evaluate the effects of 0.02% and 0.01% atropine on ocular biometrics.MethodsCohort study. 138 and 142 children were randomized to use either 0.02% or 0.01% atropine eye drops, respectively. They wore single-vision (SV) spectacles, with one drop of atropine applied to both eyes nightly. Controls (N = 120) wore only SV spectacles. Ocular and corneal astigmatism were calculated using Thibos vector analysis and split into J0 and J45.ResultsThe changes in cycloplegic spherical equivalent refraction (SER) and axial length (AL) were −0.81 ± 0.52D, −0.94 ± 0.59D, and −1.33 ± 0.72D; and 0.62 ± 0.29 mm, 0.72 ± 0.31 mm, and 0.89 ± 0.35 mm in the 0.02% and 0.01% atropine and control groups, respectively (all P 0.05). Intraocular pressure (IOP), corneal curvature, ocular astigmatism J45, and corneal astigmatism (including J0 and J45) remained stable over time in the three groups (all P > 0.05). The contributions to SER progression from the changes in AL, lens and corneal power of the three groups were similar (P > 0.05). The contribution of AL change alone to the change in SER was 56.3%, 63.4% and 78.2% in the above corresponding three groups.ConclusionsAfter 2 years, 0.02% and 0.01% atropine had no clinical effects on corneal and lens power, ocular and corneal astigmatism, ACD or IOP compared to the control group. 0.02% and 0.01% atropine helped to control myopia progression mainly by reducing AL elongation.

Purpose: To identify 24-h changes in ocular biometric parameters in subjects with ocular hypertension (OHT), and to determine if an intraocular pressure (IOP)-lowering drug alters these parameters. Methods: Thirty volunteers with OHT (58.6 ± 9.2 years of age) were enrolled in this randomized, double-masked, placebo-controlled, crossover study. Participants self-administered 0.2% brimonidine or placebo 3 times daily for 6 weeks. Measurements of seated and supine IOP, central cornea thickness (CCT), anterior chamber depth (ACD), axial length (AXL), and lens thickness were made at 8 am, 3 pm, 8 pm, and 3 am. Statistical tests were Student's 2-tailed paired t-tests or 2-way analysis of variance (ANOVA) followed by one-way ANOVA and post hoc testing. Results: Time of day had a significant effect on IOP, CCT, ACD, and AXL. In placebo-treated eyes, CCT was greater at 3 am than at any other time (P < 0.01), ACD and AXL were greater at 3 am and 8 pm than at 3 pm (P < 0.01). Daytime IOPs were higher than nighttime (seated, P = 0.007; supine, P = 0.018), and supine IOP at night was higher than seated IOP during the day (P < 0.001). Brimonidine did not lower IOP at night nor did it alter the 24-h patterns of CCT, ACD, and AXL. Conclusions: Ocular biometric parameters exhibit characteristic 24-h fluctuations in patients with OHT. At night compared with day, the supine IOP increases, the cornea thickens, the anterior chamber deepens, and the AXL increases. Brimonidine does not alter these parameters at times when it lowers IOP (day) nor when it does not (night). Clinical Trial Registration number: NCT0132419. [ABSTRACT FROM AUTHOR]

The massive availability of cameras and personal devices results in a wide variability between imaging conditions, producing large intra-class variations and a significant performance drop if images from heterogeneous environments are compared for person recognition purposes. However, as biometric solutions are extensively deployed, it will be common to replace acquisition hardware as it is damaged or newer designs appear or to exchange information between agencies or applications operating in different environments. Furthermore, variations in imaging spectral bands can also occur. For example, face images are typically acquired in the visible (VIS) spectrum, while iris images are usually captured in the near-infrared (NIR) spectrum. However, cross-spectrum comparison may be needed if, for example, a face image obtained from a surveillance camera needs to be compared against a legacy database of iris imagery. Here, we propose a multialgorithmic approach to cope with periocular images captured with different sensors. With face masks in the front line to fight against the COVID-19 pandemic, periocular recognition is regaining popularity since it is the only region of the face that remains visible. As a solution to the mentioned cross-sensor issues, we integrate different biometric comparators using a score fusion scheme based on linear logistic regression This approach is trained to improve the discriminating ability and, at the same time, to encourage that fused scores are represented by log-likelihood ratios. This allows easy interpretation of output scores and the use of Bayes thresholds for optimal decision-making since scores from different comparators are in the same probabilistic range. We evaluate our approach in the context of the 1st Cross-Spectral Iris/Periocular Competition, whose aim was to compare person recognition approaches when periocular data from visible and near-infrared images is matched. The proposed fusion approach achieves reductions in the error rates of up to 30%–40% in cross-spectral NIR–VIS comparisons with respect to the best individual system, leading to an EER of 0.2% and a FRR of just 0.47% at FAR = 0.01%. It also represents the best overall approach of the mentioned competition. Experiments are also reported with a database of VIS images from two different smartphones as well, achieving even bigger relative improvements and similar performance numbers. We also discuss the proposed approach from the point of view of template size and computation times, with the most computationally heavy comparator playing an important role in the results. Lastly, the proposed method is shown to outperform other popular fusion approaches in multibiometrics, such as the average of scores, Support Vector Machines, or Random Forest. • Multialgorithmic approach for periocular recognition using images from different sensors. • Integration of systems at the score level using linear logistic regression fusion. • Evaluation in both visible-to-visible and visible-to-near-infrared comparisons. • Comparison with popular fusion approaches employed in multibiometrics. • Best overall approach evaluated in cross-eyed periocular competitions. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the prevalence of myopia in Chinese primary school students and their ocular biometrics including axial length (AL), corneal radius of curvature (CRC) and spherical equivalent refraction (SER). To analyze their association with potential myopia risk factors, such as body mass index (BMI), cram school, time of outdoor activity and electronic screen use.Methods: In this cross-sectional study of 4500 primary school students from 5 schools, participants underwent refraction using non-cycloplegic autorefractor and visual acuity testing. A follow-up study in the same schools was conducted in 2022. Myopia was defined as SER ≤ -0.50 diopter (D) and uncorrected visual acuity (UCVA) < 0.00 logMAR (6/6). Logistic regression models were used to determine factors associated with myopia.Results: After excluding 389 participants, the overall prevalence of myopia was 33.6%. The prevalence of high myopia was 0.6%. The prevalence of myopia in girls was significantly higher than that in boys (37.6% vs. 30.0%, p < 0.001). The height, weight and BMI were significantly associated with AL (r = 0.471, r = 0.440, r = 0.276, p < 0.001, respectively). AL/CRC ratio was more highly correlated with SER than AL alone. Regression analysis showed that AL/CRC and hyperopia reserve were associated with myopia onset in the subsequent year (F = 201.557, p < 0.001; F = 68.934, p < 0.001). The cut point of hyperopia reserve for myopia in the subsequent year for grade 1 students was + 0.31D. Age (p < 0.001), parental myopia (p = 0.001) and lack of outdoor activity between classes (p = 0.049) were independently associated with higher prevalence rates of myopia.Conclusion: The prevalence of myopia among Chinese schoolchildren is alarming high. Consistent with previous cross-sectional data, AL/CRC and hyperopia reserve could function as myopia detection indicators. The hyperopia reserve among children aged between 6 ~ 7 years was low. Healthcare providers need to raise parents' awareness of the importance of regular eye examination and proper optical correction. [ABSTRACT FROM AUTHOR]

Periocular recognition has grown in popularity in biometrics applications over the years, and it is now being used in several large-scale national initiatives. Even though periocular patterns are unique, extrinsic factors like illumination, disease in the eye, camera-eye angle, and sensor interoperability can influence them. The use of contact lenses, particularly color cosmetic lenses, can complicate ocular biometrics by obscuring feature patterns and altering inter-class and intra-class distributions. This paper presents an in-depth analysis of changes in the eye (iris and sclera) color on periocular recognition performance. For this purpose, the proposed method generates an augmented dataset by masking out the ocular region (sclera and iris area) from a subject's periocular images and replacing it with other subjects' ocular regions. We simulate the uses of colored contact lenses by performing three experiments, and for each experiment, three cases are considered (recognition using the left eye, right eye, and both eyes). Statistical parameters are measured and compared to evaluate the performance, reliability, flexibility, robustness, and usability of periocular biometrics under different scenarios. [ABSTRACT FROM AUTHOR]

To assess baseline ocular biometric risk factors for progression from primary angle closure suspect (PACS) to primary angle closure (PAC) or acute angle closure (AAC). Prospective, observational study. Six hundred forty-three mainland Chinese with untreated PACS. Participants underwent baseline clinical examinations, including gonioscopy, anterior segment OCT (AS-OCT) imaging, and A-scan ultrasound biometry as part of the Zhongshan Angle Closure Prevention (ZAP) Trial. Primary angle closure suspect was defined as an inability to visualize pigmented trabecular meshwork in 2 or more quadrants based on static gonioscopy. Primary angle closure was defined as development of intraocular pressure above 24 mmHg or peripheral anterior synechiae. Progression was defined as development of PAC or an AAC attack. Multivariable logistic regression models were developed to assess biometric risk factors for progression. Six-year progression from PACS to PAC or AAC. Six hundred forty-three untreated eyes (609 nonprogressors, 34 progressors) of 643 participants were analyzed. In a multivariable model with continuous parameters, narrower horizontal angle opening distance of 500 μm from the scleral spur (AOD 500 ; odds ratio [OR], 1.10 per 0.01-mm decrease; P = 0.03), flatter horizontal iris curvature (IC; OR, 1.96 per 0.1-mm decrease; P = 0.01), and older age (OR, 1.11 per 1-year increase; P = 0.01) at baseline were associated significantly with progression (area under the receiver operating characteristic curve [AUC], 0.73). Smaller cumulative gonioscopy score was not associated with progression (OR, 1.03 per 1-modified Shaffer grade decrease; P = 0.85) when replacing horizontal AOD 500 in the multivariable model. In a separate multivariable model with categorical parameters, participants in the lowest quartile of horizontal AOD 500 (OR, 3.10; P = 0.002) and IC (OR, 2.48; P = 0.014) measurements and 59 years of age or older (OR, 2.68; P = 0.01) at baseline showed higher odds of progression (AUC, 0.72). Ocular biometric measurements can help to risk-stratify patients with early angle closure for more severe disease. Anterior segment OCT measurements of biometric parameters describing the angle and iris are predictive of progression from PACS to PAC or AAC, whereas gonioscopy grades are not. [ABSTRACT FROM AUTHOR]

The use of the iris and periocular region as biometric traits has been extensively investigated, mainly due to the singularity of the iris features and the use of the periocular region when the image resolution is not sufficient to extract iris information. In addition to providing information about an individual's identity, features extracted from these traits can also be explored to obtain other information such as the individual's gender, the influence of drug use, the use of contact lenses, spoofing, among others. This work presents a survey of the databases created for ocular recognition, detailing their protocols and how their images were acquired. We also describe and discuss the most popular ocular recognition competitions (contests), highlighting the submitted algorithms that achieved the best results using only iris trait and also fusing iris and periocular region information. Finally, we describe some relevant works applying deep learning techniques to ocular recognition and point out new challenges and future directions. Considering that there are a large number of ocular databases, and each one is usually designed for a specific problem, we believe this survey can provide a broad overview of the challenges in ocular biometrics. [ABSTRACT FROM AUTHOR]

With the advances in cataract phacoemulsification and intraocular lens implantation, more and more attention has been paid to the postoperative effects by both clinicians and patients. Meanwhile, the instruments for the preoperative measurements are also evolving. Various types of ocular biometers have emerged, which have evolved the principles from ultrasound to swept-source optical coherence tomography(SS-OCT). The OA-2000, a new type of SS-OCT based ocular biometer with fully automatic three-dimensional scanning, has the advantages of simple and safe operation, high resolution, excellent repeatability, fast measurement and good tissue penetration. It can obtain multiple ocular biological parameters in one measurement, which enables a wide application prospect. Here, we review the measurement principle and clinical application of OA-2000.

ObjectiveTo observe the associations between regional peripheral refraction and myopia development in young Chinese people.MethodsTwo hundred and forty-one young adult subjects (21 emmetropes, 88 low myopes, 94 moderate myopes, and 38 high myopes) aged 18–28 years were included, and only the right eyes were tested. Eye biometrics were measured before pupil dilation using the Lenstar. Relative peripheral refractive errors (RPRE) were measured after pupil dilation using multispectral refractive topography (MRT), at nine retinal eccentricities: 0–5, 5–10, 10–15, 15–20, 20–25, 25–30, 30–35, 35–40, and 40–45 degrees.ResultsIn this study, RPRE increased with eccentricity, and it shows a growing trend with the increase of the degree of myopia among emmetropia, low myopia and moderate myopia groups, and RPRE varied with myopia severity at eccentricities between 20 and 35 degrees only. In addition, axial length (AL) and RPRE were positively correlated between 20 and 45 degrees, and AL was an independent risk factor for RPRE between 20 and 35 degrees.ConclusionThese findings indicate that the eccentricities between 20 and 35 degrees RPRE may be closely related to refractive development and eye growth in young Chinese people.

The area of ocular biometrics is among the most popular branches of biometric recognition technology. This area has long been dominated by iris recognition research, while other ocular modalities such as the periocular region or the vasculature of the sclera have received significantly less attention in the literature. Consequently, ocular modalities beyond the iris are not well studied and their characteristics are today still not as well understood. While recent needs for more secure authentication schemes have considerably increased the interest in competing ocular modalities, progress in these areas is still held back by the lack of publicly available datasets that would allow for more targeted research into specific ocular characteristics next to the iris. In this paper, we aim to bridge this gap for the case of sclera biometrics and introduce a novel dataset designed for research into ocular biometrics and most importantly for research into the vasculature of the sclera. Our dataset, called Sclera Blood Vessels, Periocular and Iris (SBVPI), is, to the best of our knowledge, the first publicly available dataset designed specifically with research in sclera biometrics in mind. The dataset contains high-quality RGB ocular images, captured in the visible spectrum, belonging to 55 subjects. Unlike competing datasets, it comes with manual markups of various eye regions, such as the iris, pupil, canthus or eyelashes and a detailed pixel-wise annotation of the complete sclera vasculature for a subset of the images. Additionally, the datasets ship with gender and age labels. The unique characteristics of the dataset allow us to study aspects of sclera biometrics technology that have not been studied before in the literature (e.g. vasculature segmentation techniques) as well as issues that are of key importance for practical recognition systems. Thus, next to the SBVPI dataset we also present in this paper a comprehensive investigation into sclera biometrics and the main covariates that affect the performance of sclera segmentation and recognition techniques, such as gender, age, gaze direction or image resolution. Our experiments not only demonstrate the usefulness of the newly introduced dataset, but also contribute to a better understanding of sclera biometrics in general. [ABSTRACT FROM AUTHOR]

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Purpose: To assess associations between different types of electronic devices, myopic refraction and ocular biometric parameters in children aged 6–14 years in urban areas of Tianjin, China. Methods: A school‐based, cross‐sectional study was performed on 566 children (302 boys and 264 girls). The children underwent a comprehensive eye examination, including cycloplegic autorefraction and ocular biometry. The children's parents completed a detailed questionnaire that included each child's demographics, the use of electronic devices and other related risk factors. Results: Myopia was not associated with time spent using various electronic devices. However, the mean spherical equivalent refraction (SER) decreased by 0.28 D (p = 0.042) and 0.33 D (p = 0.018) for each 1‐h increase in the time spent using smart phones and computers, respectively. In the multiple linear regression analyses of factors associated with the SER, the standardised coefficient B for time spent reading and writing was approximately four to five times larger than the standardised coefficient for time spent using smart phones or computers. Time spent using tablets and watching television was not significantly associated with the SER. A longer axial length (AL) was associated with more time spent using smart phones (B = 0.23, p = 0.006) and computers (B = 0.26, p = 0.002) but not using tablets (p = 0.45) and watching television (p = 0.45). No significant association was found between other ocular biometric parameters and time spent using various electronic devices. Conclusions: On average, a more myopic SER and longer AL were both associated with more time spent using smart phones and computers, but not with time spent using tablets and watching television. The magnitude of the association between SER and time spent reading and writing was a substantially larger than that for smart phone or computer use. Different types of electronic devices had differing levels of association with myopic refraction. [ABSTRACT FROM AUTHOR]

The sclera has recently been gaining attention as a biometric modality due to its various desirable characteristics. A key step in any type of ocular biometric recognition, including sclera recognition, is the segmentation of the relevant part(s) of the eye. However, the high computational complexity of the (deep) segmentation models used in this task can limit their applicability on resource-constrained devices such as smartphones or head-mounted displays. As these devices are a common desired target for such biometric systems, lightweight solutions for ocular segmentation are critically needed. To address this issue, this paper introduces IPAD (Iterative Pruning with Activation Deviation), a novel method for developing lightweight convolutional networks, that is based on model pruning. IPAD uses a novel filter-activation-based criterion (ADC) to determine low-importance filters and employs an iterative model pruning procedure to derive the final lightweight model. To evaluate the proposed pruning procedure, we conduct extensive experiments with two diverse segmentation models, over four publicly available datasets (SBVPI, SLD, SMD and MOBIUS), in four distinct problem configurations and in comparison to state-of-the-art methods from the literature. The results of the experiments show that the proposed filter-importance criterion outperforms the standard L 1 and L 2 approaches from the literature. Furthermore, the results also suggest that: (i) the pruned models are able to retain (or even improve on) the performance of the unpruned originals, as long as they are not over-pruned, with RITnet and U-Net at 50% of their original FLOPs reaching up to 4 % and 7 % higher IoU values than their unpruned versions, respectively, (ii) smaller models require more careful pruning, as the pruning process can hurt the model's generalization capabilities, and (iii) the novel criterion most convincingly outperforms the classic approaches when sufficient training data is available, implying that the abundance of data leads to more robust activation-based importance computation. [ABSTRACT FROM AUTHOR]

Ocular biometrics in the visible spectrum has emerged as an area of significant research activity. In this paper, we propose a hybrid convolution-based model, for verifying a pair of periocular images containing the iris. We compose the hybrid model as a combination of an unsupervised and a supervised convolution neural network, and augment the combination with the well-known geometry-based Root SIFT model. We also compare the performance of both convolution-based models against each other, as well as, with the baseline Root SIFT. In the first (unsupervised w.r.t target dataset) convolution based deep learning approach, we use a stacked convolutional architecture, using external models learned a-priori on external facial and periocular data, on top of the baseline Root SIFT model applied on the provided data, and apply different score fusion models. In the second (supervised w.r.t target dataset) approach, we again use a stacked convolution architecture; but here, we learn the feature vector in a supervised manner. On the MICHE-II dataset, we obtain an AUROC of 0.946 and 0.981, and EER of 0.092 and 0.066, for the two models respectively. The hybrid model we propose, which combines these two convolutional neural networks, outperforms the constituents, in case both images arise from the same device type, but not necessarily so otherwise, obtaining a AUROC of 0.986 and EER of 0.053. We also benchmark our performance on the standard VISOB database, where we outperform the state of the art methods, achieving a TPR of 99.5% at a FPR of 0.001%. Given the robustness and significant performance of our methodology, our system can be used in practical applications with minimal error. [ABSTRACT FROM AUTHOR]

Ocular biometrics encompasses the imaging and use of characteristic features extracted from the eyes for personal recognition. Ocular biometric modalities in visible light have mainly focused on iris, blood vessel structures over the white of the eye (mostly due to conjunctival and episcleral layers), and periocular region around eye. Most of the existing studies on iris recognition use the near infrared spectrum. However, conjunctival vasculature and periocular regions are imaged in the visible spectrum. Iris recognition in the visible spectrum is possible for light color irides or by utilizing special illumination. Ocular recognition in the visible spectrum is an important research area due to factors such as recognition at a distance, suitability for recognition with regular RGB cameras, and adaptability to mobile devices. Further these ocular modalities can be obtained from a single RGB eye image, and then fused together for enhanced performance of the system. Despite these advantages, the state-of-the-art related to ocular biometrics in visible spectrum is not well known. This paper surveys this topic in terms of computational image enhancement, feature extraction, classification schemes and designed hardware-based acquisition set-ups. Future research directions are also enumerated to identify the path forward. [ABSTRACT FROM AUTHOR]

Biometrics, an integral component of Identity Science , is widely used in several large-scale-county-wide projects to provide a meaningful way of recognizing individuals. Among existing modalities, ocular biometric traits such as iris, periocular, retina, and eye movement have received significant attention in the recent past. Iris recognition is used in Unique Identification Authority of India’s Aadhaar Program and the United Arab Emirate’s border security programs, whereas the periocular recognition is used to augment the performance of face or iris when only ocular region is present in the image. This paper reviews the research progression in these modalities. The paper discusses existing algorithms and the limitations of each of the biometric traits and information fusion approaches which combine ocular modalities with other modalities. We also propose a path forward to advance the research on ocular recognition by (i) improving the sensing technology, (ii) heterogeneous recognition for addressing interoperability, (iii) utilizing advanced machine learning algorithms for better representation and classification, (iv) developing algorithms for ocular recognition at a distance, (v) using multimodal ocular biometrics for recognition, and (vi) encouraging benchmarking standards and open-source software development. [ABSTRACT FROM AUTHOR]

Background: Several studies have shown that various concentrations of low-concentration atropine can reduce myopia progression and control axial elongation safely and efficiently in children. The aim of this study was to evaluate the effects of 0.02% and 0.01% atropine on ocular biometrics., Methods: Cohort study. 138 and 142 children were randomized to use either 0.02% or 0.01% atropine eye drops, respectively. They wore single-vision (SV) spectacles, with one drop of atropine applied to both eyes nightly. Controls ( N  = 120) wore only SV spectacles. Ocular and corneal astigmatism were calculated using Thibos vector analysis and split into J0 and J45., Results: The changes in cycloplegic spherical equivalent refraction (SER) and axial length (AL) were -0.81 ± 0.52D, -0.94 ± 0.59D, and -1.33 ± 0.72D; and 0.62 ± 0.29 mm, 0.72 ± 0.31 mm, and 0.89 ± 0.35 mm in the 0.02% and 0.01% atropine and control groups, respectively (all P  < 0.05). Both anterior chamber depth (ACD) and ocular astigmatism (including J0) increased, and lens power decreased in the three groups (all P  < 0.05). However, there were no differences in the changes in ACD, ocular astigmatism, and lens power among the three groups (all P  > 0.05). Intraocular pressure (IOP), corneal curvature, ocular astigmatism J45, and corneal astigmatism (including J0 and J45) remained stable over time in the three groups (all P  > 0.05). The contributions to SER progression from the changes in AL, lens and corneal power of the three groups were similar ( P  > 0.05). The contribution of AL change alone to the change in SER was 56.3%, 63.4% and 78.2% in the above corresponding three groups., Conclusions: After 2 years, 0.02% and 0.01% atropine had no clinical effects on corneal and lens power, ocular and corneal astigmatism, ACD or IOP compared to the control group. 0.02% and 0.01% atropine helped to control myopia progression mainly by reducing AL elongation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Wang, Cui, Yu, Liang, Ma and Fu.)

Anisometropia represents a unique example of ocular development, where the two eyes of an individual, with an identical genetic background and seemingly subject to identical environmental influences, can grow asymmetrically to produce significantly different refractive errors. This review provides an overview of the research examining myopic anisometropia, the ocular characteristics underlying the condition and the potential aetiological factors involved. Various mechanical factors are discussed, including corneal structure, intraocular pressure and forces generated during near work that may contribute to development of anisomyopia. Potential visually guided mechanisms of unequal ocular growth are also explored, including the influence of astigmatism, accommodation, higher-order aberrations and the choroidal response to altered visual experience. The association between binocular vision, ocular dominance and asymmetric refraction is also considered, along with a review of the genetic contribution to the aetiology of myopic anisometropia. Despite a significant amount of research into the biomechanical, structural and optical characteristics of anisometropic eyes, there is still no unifying theory, which adequately explains how two eyes within the same visual system grow to different endpoints. [ABSTRACT FROM AUTHOR]