Publications by authors named "Junru Ren"

Due to the hardware constraints of Computed Tomography (CT) imaging, acquiring high-resolution (HR) CT images in clinical settings poses a significant challenge. In recent years, convolutional neural networks have shown great potential in CT super-resolution (SR) problems. However, the reconstruction results of many deep learning-based SR methods have structural distortion and detail ambiguity.

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In recent years, a kind of novel cellular concrete, fabricated by spherical saturated superabsorbent polymers, was developed. Its compressive behavior under high strain rate loadings has been studied by split Hopkinson pressure bar equipment in previous research, which revealed an obvious strain rate effect. It has been found by many researchers that the dynamic increase factor (DIF) of compressive strength for concrete-like materials measured by SHPB includes considerable structural effects, which cannot be considered as a genuine strain rate effect.

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Objective: The diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline.

Methods: Simulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations.

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Background: Photon counting detector computed tomography (PCD-CT) is a novel promising technique providing higher spatial resolution, lower radiation dose and greater energy spectrum differentiation, which create more possibilities to improve image quality. Multi-material decomposition is an attractive application for PCD-CT to identify complicated materials and provide accurate quantitative analysis. However, limited by the finite photon counting rate in each energy window of photon counting detector, the noise problem hinders the decomposition of high-quality basis material images.

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Background: Dual-energy computed tomography (DECT) is a promising technique, which can provide unique capability for material quantification. The iterative reconstruction of material maps requires spectral information and its accuracy is affected by spectral mismatch. Simultaneously estimating the spectra and reconstructing material maps avoids extra workload on spectrum estimation and the negative impact of spectral mismatch.

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The potential impact of renal function-related cardiovascular remodeling on associated cardiovascular risk has not been previously investigated. Hence, we conducted multiple mediation analyses in the UK Biobank study to evaluate this association. Using multiple Cox models, we found lower renal function (estimated glomerular filtration rate based on cystatin C, eGFR-cysC) was independently related to increased risks of various cardiovascular events and mortalities.

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Compared with conventional single-energy computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but most DECT imaging systems require dual full-angle projection data at different X-ray spectra. Relaxing the requirement of data acquisition is an attractive research to promote the applications of DECT in wide range areas and reduce the radiation dose as low as reasonably achievable. In this work, we design a novel DECT imaging scheme with dual quarter scans and propose an efficient method to reconstruct the desired DECT images from the dual limited-angle projection data.

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Background: Mal de Meleda is an autosomal recessive palmoplantar keratoderma, with SLURP1 identified as the pathogenic gene responsible. Although over 20 mutations in SLURP1 have been reported, only the mutation c.256G > A (p.

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Purpose: Low-dose computed tomography (LDCT) has promising potential for dose reduction in medical applications, while suffering from low image quality caused by noise. Therefore, it is in urgent need for developing new algorithms to obtain high-quality images for LDCT.

Methods: This study tries to exploit the sparse and low-rank properties of images and proposes a new algorithm based on subspace identification.

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Nagashima-type palmoplantar keratosis (NPPK) is a diffuse, autosomal recessive, and non-epidermolytic palmoplantar keratosis caused by mutations in the SERPINB7 gene, a member of the serine protease inhibitor superfamily. Genetic studies and case reports suggest that NPPK is the most common palmoplantar keratosis in East Asia but rare in Western countries. This study reports eight NPPK patients in seven pedigrees of the Chinese Han ethnicity with two novel (c.

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Goal: The aim of this study is to find a kind of low frequency oscillation transcranial alternating current stimulation, which is directly applied to the scalp epidermal, to stimulate the cerebral cortex with a large spatial range of electric field oscillation across the brain hemisphere, and then trigger the start of the Top-Down processing of sleep homeostasis, in the daytime nap.

Methods: Thirty healthy subjects, to take naps, underwent an intervention of electrical stimulation at 5 Hz, applied to the dorsal lateral prefrontal cortex. The subjects in the experiments were strictly controlled, and opened their eyes when stimulation was transmitted.

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