Data Driven Coded Aperture Design for Depth Recovery

Inserting a patterned occluder at the aperture of a camera lens has been shown to improve the recovery of depth map and all-focus image compared to a fully open aperture. However, design of the aperture pattern plays a very critical role. Previous approaches for designing aperture codes make simple assumptions on image distributions to obtain metrics for evaluating aperture codes. However, real images may not follow those assumptions and hence the designed code may not be optimal for them. To address this drawback we propose a data driven approach for learning the optimal aperture pattern to recover depth map from a single coded image. We propose a two stage architecture where, in the first stage we simulate coded aperture images from a training dataset of all-focus images and depth maps and in the second stage we recover the depth map using a deep neural network. We demonstrate that our learned aperture code performs better than previously designed codes even on code design metrics proposed by previous approaches.Comment: 5 pages, 4 figures. Accepted at IEEE ICIP 2017, Beijing, Chin

Modeling the relative influence of socio-demographic variables on post-acute COVID-19 quality of life

Importance: Post-acute sequelae of SARS-CoV-2, referred to as “long COVID”, are a globally pervasive threat. While their many clinical determinants are commonly considered, their plausible social correlates are often overlooked. Objective: To compare social and clinical predictors of differences in quality of life (QoL) with long COVID. Additionally, to measure how much adjusted associations between social factors and long COVID-associated quality of life are unexplained by important clinical intermediates. Design, Setting, and Participants: Data from the ISARIC long COVID multi-country prospective cohort study. Subjects from Norway, the United Kingdom (UK), and Russia, aged 16 and above, with confirmed acute SARS-CoV-2 infection reporting >= 1 long COVID-associated symptoms 1+ month following infection. Exposure: The social exposures considered were educational attainment (Norway), employment status (UK and Russia), and female vs male sex (all countries). Main outcome and measures: Quality of life-adjusted days, or QALDs, with long COVID. Results: This cohort study included a total of 3891 participants. In all three countries, educational attainment, employment status, and female sex were important predictors of long COVID QALDs. Furthermore, a majority of the estimated relationships between each of these social correlates and long COVID QALDs could not be attributed to key long COVID-predicting comorbidities. In Norway, 90% (95% CI: 77%, 100%) of the adjusted association between the top two quintiles of educational attainment and long COVID QALDs was not explained by clinical intermediates. The same was true for 86% (73%, 100%) and 93% (80%,100%) of the adjusted associations between full-time employment and long COVID QALDs in the United Kingdom (UK) and Russia. Additionally, 77% (46%,100%) and 73% (52%, 94%) of the adjusted associations between female sex and long COVID QALDs in Norway and the UK were unexplained by the clinical mediators. Conclusions and Relevance: This study highlights the role of socio-economic status indicators and female sex, in line with or beyond commonly cited clinical conditions, as predictors of long COVID-associated QoL, and further reveal that other (non-clinical) mechanisms likely drive their observed relationships. Our findings point to the importance of COVID interventions which go further than an exclusive focus on comorbidity management in order to help redress inequalities in experiences with this chronic disease. Question: How do social and medical factors compare in predicting differences in quality of life (QoL) with long COVID and to what extent do clinical mediators explain social variables’ relationships with long COVID QoL? Findings: Socio-economic proxies employment status and educational attainment and female sex ranked on par with or above age and neuropsychological and rheumatological comorbidities as predictors of variation in long COVID QoL across participants. Additionally, estimated adjusted associations between each of these social factors and long COVID QoL were largely unexplained by a set of key comorbidities. Meaning: Long COVID-based interventions may be more broadly beneficial if they account for social disparities as important risk factors for differential long COVID burden and, in addition to clinical targets, address broader structural determinants of health

Neurological manifestations of COVID-19 in adults and children

Different neurological manifestations of coronavirus disease 2019 (COVID-19) in adults and children and their impact have not been well characterized. We aimed to determine the prevalence of neurological manifestations and in-hospital complications among hospitalized COVID-19 patients and ascertain differences between adults and children. We conducted a prospective multicentre observational study using the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) cohort across 1507 sites worldwide from 30 January 2020 to 25 May 2021. Analyses of neurological manifestations and neurological complications considered unadjusted prevalence estimates for predefined patient subgroups, and adjusted estimates as a function of patient age and time of hospitalization using generalized linear models. Overall, 161 239 patients (158 267 adults; 2972 children) hospitalized with COVID-19 and assessed for neurological manifestations and complications were included. In adults and children, the most frequent neurological manifestations at admission were fatigue (adults: 37.4%; children: 20.4%), altered consciousness (20.9%; 6.8%), myalgia (16.9%; 7.6%), dysgeusia (7.4%; 1.9%), anosmia (6.0%; 2.2%) and seizure (1.1%; 5.2%). In adults, the most frequent in-hospital neurological complications were stroke (1.5%), seizure (1%) and CNS infection (0.2%). Each occurred more frequently in intensive care unit (ICU) than in non-ICU patients. In children, seizure was the only neurological complication to occur more frequently in ICU versus non-ICU (7.1% versus 2.3%, P < 0.001). Stroke prevalence increased with increasing age, while CNS infection and seizure steadily decreased with age. There was a dramatic decrease in stroke over time during the pandemic. Hypertension, chronic neurological disease and the use of extracorporeal membrane oxygenation were associated with increased risk of stroke. Altered consciousness was associated with CNS infection, seizure and stroke. All in-hospital neurological complications were associated with increased odds of death. The likelihood of death rose with increasing age, especially after 25 years of age. In conclusion, adults and children have different neurological manifestations and in-hospital complications associated with COVID-19. Stroke risk increased with increasing age, while CNS infection and seizure risk decreased with age