DeMoN: Depth and Motion Network for Learning Monocular Stereo

In this paper we formulate structure from motion as a learning problem. We train a convolutional network end-to-end to compute depth and camera motion from successive, unconstrained image pairs. The architecture is composed of multiple stacked encoder-decoder networks, the core part being an iterative network that is able to improve its own predictions. The network estimates not only depth and motion, but additionally surface normals, optical flow between the images and confidence of the matching. A crucial component of the approach is a training loss based on spatial relative differences. Compared to traditional two-frame structure from motion methods, results are more accurate and more robust. In contrast to the popular depth-from-single-image networks, DeMoN learns the concept of matching and, thus, better generalizes to structures not seen during training.Comment: Camera ready version for CVPR 2017. Supplementary material included. Project page: http://lmb.informatik.uni-freiburg.de/people/ummenhof/depthmotionnet

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

Recent work has shown that optical flow estimation can be formulated as a supervised learning task and can be successfully solved with convolutional networks. Training of the so-called FlowNet was enabled by a large synthetically generated dataset. The present paper extends the concept of optical flow estimation via convolutional networks to disparity and scene flow estimation. To this end, we propose three synthetic stereo video datasets with sufficient realism, variation, and size to successfully train large networks. Our datasets are the first large-scale datasets to enable training and evaluating scene flow methods. Besides the datasets, we present a convolutional network for real-time disparity estimation that provides state-of-the-art results. By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network.Comment: Includes supplementary materia

Analysis of transcribed human endogenous retrovirus W env loci clarifies the origin of multiple sclerosis-associated retrovirus env sequences

<p>Abstract</p> <p>Background</p> <p>Multiple sclerosis-associated retrovirus (MSRV) RNA sequences have been detected in patients with multiple sclerosis (MS) and are related to the multi-copy human endogenous retrovirus family type W (HERV-W). Only one HERV-W locus (ERVWE1) codes for a complete HERV-W Env protein (Syncytin-1). Syncytin-1 and the putative MSRV Env protein have been involved in the pathogenesis of MS. The origin of MSRV and its precise relation to HERV-W were hitherto unknown.</p> <p>Results</p> <p>By mapping HERV-W <it>env </it>cDNA sequences (n = 332) from peripheral blood mononuclear cells of patients with MS and healthy controls onto individual genomic HERV-W <it>env </it>elements, we identified seven transcribed HERV-W <it>env </it>loci in these cells, including ERVWE1. Transcriptional activity of individual HERV-W <it>env </it>elements did not significantly differ between patients with MS and controls. Remarkably, almost 30% of HERV-W <it>env </it>cDNAs were recombined sequences that most likely arose <it>in vitro </it>between transcripts from different HERV-W <it>env </it>elements. Re-analysis of published MSRV <it>env </it>sequences revealed that all of them can be explained as originating from genomic HERV-W <it>env </it>loci or recombinations among them. In particular, a MSRV <it>env </it>clone previously used for the generation of monoclonal antibody 6A2B2, detecting an antigen in MS brain lesions, appears to be derived from a HERV-W <it>env </it>locus on chromosome Xq22.3. This locus harbors a long open reading frame for an N-terminally truncated HERV-W Env protein.</p> <p>Conclusion</p> <p>Our data clarify the origin of MSRV <it>env </it>sequences, have important implications for the status of MSRV, and open the possibility that a protein encoded by a HERV-W <it>env </it>element on chromosome Xq22.3 may be expressed in MS brain lesions.</p

Microbial keratitis-induced endophthalmitis: incidence, symptoms, therapy, visual prognosis and outcomes

Background: To evaluate symptoms, therapies and outcomes in rare microbial keratitis-induced endophthalmitis. Methods: Retrospective study with 11 patients treated between 2009 and 2014. Clinical findings, corneal diseases, history of steroids and trauma, use of contact lenses, number and type of surgical interventions, determination of causative organisms and visual acuity (VA) were evaluated. Results: The incidence of transformation from microbial keratitis to an endophthalmitis was 0.29% (n = 11/3773). In 90.9% (n = 10/11), there were pre-existent eyelid and corneal problems, in 45.5% (n = 5/11) rubeosis iridis with increased intraocular pressure and corneal decompensation, and in 18.2% (n = 2/11), ocular trauma. Specimens could be obtained in 10 of 11 samples: 33.3% of those 10 specimens were Gram-positive coagulase-negative Staphylococci (n = 3/10) or Gram-negative rods (n = 3/10) and 10.0% Staphylococcus aureus (n = 1/10). In 30% (n = 3/10), no pathogens were identifiable. 72.7% (n = 8/11) of all keratitis-induced endophthalmitis were treated with vitrectomy and 9.1% (n = 1/11) with amniotic-membrane transplantation. In 27.3% (n = 3/11) the infected eye had to be enucleated – 18.2% (n = 2/11) primarily, 9.1% (n = 1/11) secondarily. No patient suffered from sympathetic ophthalmia. The median initial VA was 2.1 logMAR (n = 11/11). At one month, median VA was 2.0 logMAR (n = 7/11), after three months 2.0 logMAR (n = 6/11), and after one year 2.05 logMAR (n = 6/11). The change in VA was not significant (p &gt; 0.99). 36.4% (n = 4/11) of the cases resulted in blindness. Conclusions: The overall outcome is poor. Enucleation should be weighed against the risk of local and systemic spread of the infection, prolonged rehabilitation and sympathetic ophthalmia

Human endogenous retrovirus HERV-K(HML-2) encodes a stable signal peptide with biological properties distinct from Rec

<p>Abstract</p> <p>Background</p> <p>The human endogenous retrovirus HERV-K(HML-2) family is associated with testicular germ cell tumors (GCT). Various HML-2 proviruses encode viral proteins such as Env and Rec.</p> <p>Results</p> <p>We describe here that HML-2 Env gives rise to a 13 kDa signal peptide (SP) that harbors a different C-terminus compared to Rec. Subsequent to guiding Env to the endoplasmatic reticulum (ER), HML-2 SP is released into the cytosol. Biochemical analysis and confocal microscopy demonstrated that similar to Rec, SP efficiently translocates to the granular component of nucleoli. Unlike Rec, SP does not shuttle between nucleus and cytoplasm. SP is less stable than Rec as it is subjected to proteasomal degradation. Moreover, SP lacks export activity towards HML-2 genomic RNA, the main function of Rec in the original viral context, and SP does not interfere with Rec's RNA export activity.</p> <p>Conclusion</p> <p>SP is a previously unrecognized HML-2 protein that, besides targeting and translocation of Env into the ER lumen, may exert biological functions distinct from Rec. HML-2 SP represents another functional similarity with the closely related Mouse Mammary Tumor Virus that encodes an Env-derived SP named p14. Our findings furthermore support the emerging concept of bioactive SPs as a conserved retroviral strategy to modulate their host cell environment, evidenced here by a "retroviral fossil". While the specific role of HML-2 SP remains to be elucidated in the context of human biology, we speculate that it may be involved in immune evasion of GCT cells or tumorigenesis.</p

3D Heads-Up Display vs. Standard Operating Microscope Vitrectomy for Rhegmatogenous Retinal Detachment

Purpose: To assess the efficacy and outcomes of 23-gauge vitreoretinal surgery for rhegmatogenous retinal detachment using a three-dimensional heads-up display (3D HUD) surgical platform as compared to a standard operating microscope (SOM) setting. Design: Retrospective cohort study. Participants: One hundred and forty consecutive eyes of 140 patients with primary retinal detachment. Methods: All eyes underwent 23-gauge pars plana vitrectomy for primary retinal detachment using either a 3D HUD (NGENUITY;Alcon Inc., Fort Worth, Texas, USA;n = 70 eyes) or a SOM setting (n = 70 eyes);in cases of significant cataract, additional phacoemulsification with intraocular lens (IOL) implantation was performed. Minimum follow-up was 2 months. Main Outcome Measures: Primary retinal reattachment rate, rate of proliferative vitreoretinopathy (PVR), best-corrected visual acuity (BCVA), and duration of surgery. Results: There were 70 eyes each in the 3D HUD and the SOM group. Both groups did not differ concerning age (p = 0.70), extent of retinal detachment (p = 0.07), number of retinal tears (p = 0.40), macular involvement (p = 0.99), and preoperative BCVA (p = 0.99). Postoperatively, 3D HUD and SOM were comparable concerning the primary retinal reattachment rate (88.6 vs. 94.3%;p = 0.37), the development of postoperative PVR (12.9% vs. 7.1%;p = 0.40) and final BCVA (0.26 +/- 0.40 vs. 0.21 +/- 0.38 logMAR;p = 0.99). Duration of surgery was significantly longer in the 3D HUD group (66.2 +/- 16.5 vs. 61.2 +/- 17.1 min;p = 0.04), an effect which however vanished after a "learning curve" of the first 35 eyes (p = 0.49). Conclusions: On par results to a conventional operating microscope can be achieved with a 3D HUD setting when performing 23-gauge vitreoretinal surgery for rhegmatogenous retinal detachment, including the primary retinal reattachment rate, the incidence of postoperative PVR and final BCVA. However, duration of surgery might initially be slightly longer with 3D HUD, suggesting the effect of a learning curve

Intraocular Lens Power Calculation after Small Incision Lenticule Extraction

With more than 1.5 million Small Incision Lenticule Extraction (SMILE) procedures having already been performed worldwide in an ageing population, intraocular lens (IOL) power calculation in post-SMILE eyes will inevitably become a common challenge for ophthalmologists. Since no refractive outcomes of cataract surgery following SMILE have been published, there is a lack of empirical data for optimizing IOL power calculation. Using the ray tracing as the standard of reference - a purely physical method that obviates the need for any empirical optimization - we analyzed the agreement of various IOL power calculation formulas derived from the American Society of Cataract and Refractive Surgeons (ASCRS) post-keratorefractive surgery online calculator. In our study of 88 post-SMILE eyes, the Masket formula showed the smallest mean prediction error [-0.36 +/- 0.32 diopters (D)] and median absolute error (0.33D) and yielded the largest percentage of eyes within +/- 0.50D (70%) in reference to ray tracing. Non-inferior refractive prediction errors and +/- 0.50D accuracies were achieved by the Barrett True K, Barrett True K No History and the Potvin-Hill formula. Use of these formulas in conjunction with ray tracing is recommended until sufficient data for empirical optimization of IOL power calculation after SMILE is available