A nonlocal prior in iterative CT reconstruction.

Background: Computed tomography (CT) reconstruction problems are always framed as inverse problems, where the attenuation map of an imaged object is reconstructed from the sinogram measurement. In practice, these inverse problems are often ill-posed, especially under few-view and limited-angle conditions, which makes accurate reconstruction challenging. Existing solutions use regularizations such as total variation to steer reconstruction algorithms to the most plausible result.

Temporal change in minimum mortality temperature under changing climate: A multicountry multicommunity observational study spanning 1986-2015.

Background: The minimum mortality temperature (MMT) or MMT percentile (MMTP) is an indicator of population susceptibility to nonoptimum temperatures. MMT and MMTP change over time; however, the changing directions show region-wide heterogeneity. We examined the heterogeneity of temporal changes in MMT and MMTP across multiple communities and in multiple countries.

Temperature-mortality associations by age and cause: a multi-country multi-city study.

Background: Heterogeneity in temperature-mortality relationships across locations may partly result from differences in the demographic structure of populations and their cause-specific vulnerabilities. Here we conduct the largest epidemiological study to date on the association between ambient temperature and mortality by age and cause using data from 532 cities in 33 countries.

Methods: We collected daily temperature and mortality data from each country.

RBP-DIP: Residual back projection with deep image prior for ill-posed CT reconstruction.

The success of deep image prior (DIP) in a number of image processing tasks has motivated their application in image reconstruction problems in computed tomography (CT). In this paper, we introduce a residual back projection technique (RBP) that improves the performance of deep image prior framework in iterative CT reconstruction, especially when the reconstruction problem is highly ill-posed. The RBP-DIP framework uses an untrained U-net in conjunction with a novel residual back projection connection to minimize the objective function while improving reconstruction accuracy.

Climatic comparison of surface urban heat island using satellite remote sensing in Tehran and suburbs.

In this study, we aim to compare the climatic conditions of Surface Urban Heat Island (SUHI) in Tehran and its suburbs using day/night time data from three satellites. A high-resolution Land Surface Temperature (LST) data from MODIS Aqua, Sentinel-3, and Landsat 8 were selected to facilitate this study. The highest values of LST/UHI are observed in downtown Tehran and suburban areas at night.

Joint effect of heat and air pollution on mortality in 620 cities of 36 countries.

Background: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent.

Objectives: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries.

Methods: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM), PM ≤ 2.

Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis.

Objective: To investigate potential interactive effects of fine particulate matter (PM) and ozone (O) on daily mortality at global level.

Design: Two stage time series analysis.

Setting: 372 cities across 19 countries and regions.

Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

Background: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths.

Methods: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019.

Sparse-view and limited-angle CT reconstruction with untrained networks and deep image prior.

Background And Objective: Neural network based image reconstruction methods are becoming increasingly popular. However, limited training data and the lack of theoretical guarantees for generalizability raised concerns, especially in biomedical imaging applications. These challenges are known to lead to an unstable reconstruction process that poses significant problems in biomedical image reconstruction.

Effect modification of greenness on the association between heat and mortality: A multi-city multi-country study.

Background: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting.

Global, regional, and national burden of mortality associated with short-term temperature variability from 2000-19: a three-stage modelling study.

Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions.

Fluctuating temperature modifies heat-mortality association around the globe.

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries.

Exact gram filtering and efficient backprojection for iterative CT reconstruction.

Purpose: Forward and backprojections are the basis of all model-based iterative reconstruction (MBIR) methods. However, computing these accurately is time-consuming. In this paper, we present a method for MBIR in parallel X-ray beam geometry that utilizes a Gram filter to efficiently implement forward and backprojection.

Geographical Variations of the Minimum Mortality Temperature at a Global Scale: A Multicountry Study.

Background: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.

Methods: We collected data from 658 communities in 43 countries under different climates.

Mortality risk attributable to wildfire-related PM pollution: a global time series study in 749 locations.

Background: Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM and mortality across various regions of the world.

Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study.

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures.

Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe.

Direct Volume Rendering with Nonparametric Models of Uncertainty.

We present a nonparametric statistical framework for the quantification, analysis, and propagation of data uncertainty in direct volume rendering (DVR). The state-of-the-art statistical DVR framework allows for preserving the transfer function (TF) of the ground truth function when visualizing uncertain data; however, the existing framework is restricted to parametric models of uncertainty. In this paper, we address the limitations of the existing DVR framework by extending the DVR framework for nonparametric distributions.

Exposure to suboptimal ambient temperature during specific gestational periods and adverse outcomes in mice.

Exposure to suboptimal ambient temperature during pregnancy has been reported as a potential teratogen of fetal development. However, limited animal evidence is available regarding the impact of extreme temperatures on maternal pregnancy and the subsequent adverse pregnancy outcomes. Our objective in this study is to investigate the relationship between temperature and maternal stress during pregnancy in mice.

Utilizing daily excessive concentration hours to estimate cardiovascular mortality and years of life lost attributable to fine particulate matter in Tehran, Iran.

Background: Evidence for associations between fine particulate matter (PM) and cardiovascular diseases (CVDs) in Iran is scarce. Given large within-day variations of PM concentration, using the daily mean of PM (PMmean) as exposure metric might bias the health-related assessment. This study applied a novel indicator, daily excessive concentration hours (DECH), to evaluate the effect of ambient PM on CVD mortality and years of life lost (YLL) in Tehran, the capital city of Iran.

A geometric framework for ensemble average propagator reconstruction from diffusion MRI.

Diffusion-weighted magnetic resonance imaging (dMRI) is a non-invasive technique to probe the complex micro-architecture of the tissue being imaged. The diffusional properties of the tissue at the imaged resolution are well captured by the ensemble average propagator (EAP), which is a probability density function characterizing the probability of water molecule diffusion. Many properties in the form of imaging 'stains' can then be computed from the EAP that can serve as bio-markers for a variety of diseases.

Exploiting structural redundancy in q-space for improved EAP reconstruction from highly undersampled (k, q)-space in DMRI.

Accurate reconstruction of the ensemble average propagators (EAPs) from undersampled diffusion MRI (dMRI) measurements is a well-motivated, actively researched problem in the field of dMRI acquisition and analysis. A number of approaches based on compressed sensing (CS) principles have been developed for this problem, achieving a considerable acceleration in the acquisition by leveraging sparse representations of the signal. Most recent methods in literature apply undersampling techniques in the (k, q)-space for the recovery of EAP in the joint (x, r)-space.