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We present a novel algorithm performing projective rectification which does not require explicit computation of the epipolar geometry, and specifically of the fundamental matrix. Instead ofjinding the epipoles and computing two homographies mapping the epipoles to infinity, as done in recent work on projective rectification, we exploit the fact that the fundamental matrix of a pair of rectified images has a particular, known f o r m This allows us to set up a minimization that yields the rectijjing homographies directly from image correspondences. Experimental results show that our method works quite robustly even in the presence of noise, and with inaccurate point correspondences. The code of our implementation will be made available at the author's web site.

A genetic contribution to refractive error has been confirmed by the discovery of more than 150 associated variants in genome-wide association studies (GWAS). Environmental factors such as education and time outdoors also demonstrate strong associations. Currently however, the extent of gene-environment or gene-gene interactions in myopia is unknown. We tested the hypothesis that refractive error-associated variants exhibit effect size heterogeneity, a hallmark feature of genetic interactions. Of 146 variants tested, evidence of non-uniform, non-linear effects were observed for 66 (45%) at Bonferroni-corrected significance ( P < 1.1 × 10 −4 ) and 128 (88%) at nominal significance ( P < 0.05). LAMA2 variant rs12193446, for example, had an effect size varying from −0.20 diopters (95% CI −0.18 to −0.23) to −0.89 diopters (95% CI −0.71 to −1.07) in different individuals. SNP effects were strongest at the phenotype extremes and weaker in emmetropes. A parsimonious explanation for these findings is that gene-environment or gene-gene interactions in myopia are pervasive.

We present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. The algorithm is an adaptive, multiwindow scheme using left–right consistency to compute disparity and its associated uncertainty. We demonstrate and discuss performances with both synthetic and real stereo pairs, and show how our results improve on those of closely related techniques for both accuracy and efficiency.

The diagnosis of multiple sclerosis is based on a combination of clinical and paraclinical tests. The potential contribution of retinal optical coherence tomography (OCT) has been recognized. We tested the feasibility of OCT measures of retinal asymmetry as a diagnostic test for multiple sclerosis at the community level. In this community-based study of 72 120 subjects, we examined the diagnostic potential of the inter-eye difference of inner retinal OCT data for multiple sclerosis using the UK Biobank data collected at 22 sites between 2007 and 2010. OCT reporting and quality control guidelines were followed. The inter-eye percentage difference (IEPD) and inter-eye absolute difference (IEAD) were calculated for the macular retinal nerve fibre layer (RNFL), ganglion cell inner plexiform layer (GCIPL) complex and ganglion cell complex. Area under the receiver operating characteristic curve (AUROC) comparisons were followed by univariate and multivariable comparisons accounting for a large range of diseases and co-morbidities. Cut-off levels were optimized by ROC and the Youden index. The prevalence of multiple sclerosis was 0.0023 [95% confidence interval (CI) 0.00229–0.00231]. Overall the discriminatory power of diagnosing multiple sclerosis with the IEPD AUROC curve (0.71, 95% CI 0.67–0.76) and IEAD (0.71, 95% CI 0.67–0.75) for the macular GCIPL complex were significantly higher if compared to the macular ganglion cell complex IEPD AUROC curve (0.64, 95% CI 0.59–0.69, P = 0.0017); IEAD AUROC curve (0.63, 95% CI 0.58–0.68, P &lt; 0.0001) and macular RNFL IEPD AUROC curve (0.59, 95% CI 0.54–0.63, P &lt; 0.0001); IEAD AUROC curve (0.55, 95% CI 0.50–0.59, P &lt; 0.0001). Screening sensitivity levels for the macular GCIPL complex IEPD (4% cut-off) were 51.7% and for the IEAD (4 μm cut-off) 43.5%. Specificity levels were 82.8% and 86.8%, respectively. The number of co-morbidities was important. There was a stepwise decrease of the AUROC curve from 0.72 in control subjects to 0.66 in more than nine co-morbidities or presence of neuromyelitis optica spectrum disease. In the multivariable analyses greater age, diabetes mellitus, other eye disease and a non-white ethnic background were relevant confounders. For most interactions, the effect sizes were large (partial ω2 &gt; 0.14) with narrow confidence intervals. In conclusion, the OCT macular GCIPL complex IEPD and IEAD may be considered as supportive measurements for multiple sclerosis diagnostic criteria in a young patient without relevant co-morbidity. The metric does not allow separation of multiple sclerosis from neuromyelitis optica. Retinal OCT imaging is accurate, rapid, non-invasive, widely available and may therefore help to reduce need for invasive and more costly procedures. To be viable, higher sensitivity and specificity levels are needed.