Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks

Magnetic resonance image (MRI) in high spatial resolution provides detailed anatomical information and is often necessary for accurate quantitative analysis. However, high spatial resolution typically comes at the expense of longer scan time, less spatial coverage, and lower signal to noise ratio (SNR). Single Image Super-Resolution (SISR), a technique aimed to restore high-resolution (HR) details from one single low-resolution (LR) input image, has been improved dramatically by recent breakthroughs in deep learning. In this paper, we introduce a new neural network architecture, 3D Densely Connected Super-Resolution Networks (DCSRN) to restore HR features of structural brain MR images. Through experiments on a dataset with 1,113 subjects, we demonstrate that our network outperforms bicubic interpolation as well as other deep learning methods in restoring 4x resolution-reduced images.Comment: Accepted by ISBI'1

UperFormer: A Multi-scale Transformer-based Decoder for Semantic Segmentation

While a large number of recent works on semantic segmentation focus on designing and incorporating a transformer-based encoder, much less attention and vigor have been devoted to transformer-based decoders. For such a task whose hallmark quest is pixel-accurate prediction, we argue that the decoder stage is just as crucial as that of the encoder in achieving superior segmentation performance, by disentangling and refining the high-level cues and working out object boundaries with pixel-level precision. In this paper, we propose a novel transformer-based decoder called UperFormer, which is plug-and-play for hierarchical encoders and attains high quality segmentation results regardless of encoder architecture. UperFormer is equipped with carefully designed multi-head skip attention units and novel upsampling operations. Multi-head skip attention is able to fuse multi-scale features from backbones with those in decoders. The upsampling operation, which incorporates feature from encoder, can be more friendly for object localization. It brings a 0.4% to 3.2% increase compared with traditional upsampling methods. By combining UperFormer with Swin Transformer (Swin-T), a fully transformer-based symmetric network is formed for semantic segmentation tasks. Extensive experiments show that our proposed approach is highly effective and computationally efficient. On Cityscapes dataset, we achieve state-of-the-art performance. On the more challenging ADE20K dataset, our best model yields a single-scale mIoU of 50.18, and a multi-scale mIoU of 51.8, which is on-par with the current state-of-art model, while we drastically cut the number of FLOPs by 53.5%. Our source code and models are publicly available at: https://github.com/shiwt03/UperForme

Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network

High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI conventionally comes at the cost of longer scan time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent studies have shown that single image super-resolution (SISR), a technique to recover HR details from one single low-resolution (LR) input image, could provide high-quality image details with the help of advanced deep convolutional neural networks (CNN). However, deep neural networks consume memory heavily and run slowly, especially in 3D settings. In this paper, we propose a novel 3D neural network design, namely a multi-level densely connected super-resolution network (mDCSRN) with generative adversarial network (GAN)-guided training. The mDCSRN quickly trains and inferences and the GAN promotes realistic output hardly distinguishable from original HR images. Our results from experiments on a dataset with 1,113 subjects show that our new architecture beats other popular deep learning methods in recovering 4x resolution-downgraded im-ages and runs 6x faster.Comment: 10 pages, 2 figures, 2 tables. MICCAI 201

An Electromagnetically Excited Silicon Nitride Beam Resonant Accelerometer

A resonant microbeam accelerometer of a novel highly symmetric structure based on MEMS bulk-silicon technology is proposed and some numerical modeling results for this scheme are presented. The accelerometer consists of two proof masses, four supporting hinges, two anchors, and a vibrating triple beam, which is clamped at both ends to the two proof masses. LPCVD silicon rich nitride is chosen as the resonant triple beam material, and parameter optimization of the triple-beam structure has been performed. The triple beam is excited and sensed electromagnetically by film electrodes located on the upper surface of the beam. Both simulation and experimental results show that the novel structure increases the scale factor of the resonant accelerometer, and ameliorates other performance issues such as cross axis sensitivity of insensitive input acceleration, etc

An equity evaluation in stroke inpatients in regard to medical costs in China: a nationwide study.

BackgroundStroke has always been a severe disease and imposed heavy financial burden on the health system. Equity in patients in regard to healthcare utilization and medical costs are recognized as a significant factor influencing medical quality and health system responsiveness. The aim of this study is to understand the equity in stroke patients concerning medical costs and healthcare utilization, as well as identify potential factors contributing to geographic variation in stroke patients' healthcare utilization and costs.MethodsCovering 31 provinces in mainland China, our main data were a 5% random sample of stroke claims from Urban Employees Basic Medical Insurance (UEBMI) and Urban Residents Basic Medical Insurance (URBMI) from 2013 to 2016. The Theil index was employed to evaluate the equity in stroke patients in regard to healthcare utilization and medical costs, and the random-effect panel model was used to explore the impact of province-level factors (health resource factors, enabling factors, and economic factors) on medical costs and health care utilization.ResultsStroke patients' healthcare utilization and medical costs showed significant differences both within and between regions. The UEBMI scheme had an overall lower Theil index value than the URBMI scheme. The intra-region Theil index value was higher than the inter-region Theil index, with the Theil index highest within eastern China, China's richest and most developed region. Health resource factors and enabling factors (represented by reimbursement rate and education attainment years) were identified significantly associated with medical costs (P ConclusionsChina's fragmented urban health insurance schemes require further reform to ensure better equity in healthcare utilization and medical costs for stroke patients. Improving education attainment, offering equal access to healthcare, allocating health resources reasonably and balancing health services prices in different regions also count

Medical costs and hospital utilization for hemophilia A and B urban inpatients in China: a national cross-sectional study

BACKGROUND: Hemophilia care in mainland China has been greatly improved since the establishment of the Hemophilia Treatment Center Collaborative Network of China (HTCCNC), and most of drugs for hemophilia have been covered by basic medical insurance schemes. This study assesses whether medical costs and hospital utilization disparities exist between hemophilia A and hemophilia B urban inpatients in China and, second, whether the prescription of coagulation factor concentrates for hemophilia A and hemophilia B inpatients was optimal, from the third payer perspective. METHODS: We conducted a retrospective nationwide analysis based on a 5% random sample from claims data of China Urban Employees’ Basic Medical Insurance (UEBMI) and Urban Residents’ Basic Medical Insurance (URBMI) schemes from 2010 to 2016. Univariate analysis and multiple regression analysis based on a generalized linear model were conducted. RESULT: A total of 487 urban inpatients who had hemophilia were identified, including 407 inpatients with hemophilia A and 80 inpatients with hemophilia B. Total medical cost for hemophilia B inpatients was significantly higher than for hemophilia A inpatients (USD 2912.81 versus USD 1225.60, P < 0.05), and hemophilia B inpatients had a significantly longer length of hospital stay than hemophilia A inpatients (9.00 versus 7.00, P < 0.05). Total medical costs were mostly allocated to coagulation factor products (76.86-86.68%), with coagulation factor cost of hemophilia B significantly higher than hemophilia A (P < 0.05). Both hemophilia cohorts utilized greatest amount of plasma-derived Factor VIII, followed by recombinant Factor VIII and prothrombin complex concentrates. CONCLUSIONS: Patients with hemophilia B experienced significantly higher inpatient cost, coagulation factor cost and longer length of hospital stay than patients with hemophilia A. Our findings revealed the suboptimal use of coagulation factor concentrate drugs and a higher drug cost burden incurred by hemophilia B than hemophilia A inpatients. Our results call for efforts to strengthen drug regulatory management for hemophilia and to optimize medical insurance schemes according to hemophilia types

Several Critical Cell Types, Tissues, and Pathways Are Implicated in Genome-Wide Association Studies for Systemic Lupus Erythematosus

We aimed to elucidate the cell types, tissues, and pathways influenced by common variants in systemic lupus erythematosus (SLE). We applied a nonparameter enrichment statistical approach, termed SNPsea, in 181 single nucleotide polymorphisms (SNPs) that have been identified to be associated with the risk of SLE through genome-wide association studies (GWAS) in Eastern Asian and Caucasian populations, to manipulate the critical cell types, tissues, and pathways. In the two most significant cells’ findings (B lymphocytes and CD14+ monocytes), we subjected the GWAS association evidence in the Han Chinese population to an enrichment test of expression quantitative trait locus (QTL) sites and DNase I hypersensitivity, respectively. In both Eastern Asian and Caucasian populations, we observed that the expression level of SLE GWAS implicated genes was significantly elevated in xeroderma pigentosum B cells (P ≤ 1.00 × 10−6), CD14+ monocytes (P ≤ 2.74 × 10−4) and CD19+ B cells (P ≤ 2.00 × 10−6), and plasmacytoid dendritic cells (pDCs) (P ≤ 9.00 × 10−6). We revealed that the SLE GWAS-associated variants were more likely to reside in expression QTL in B lymphocytes (q1/q0 = 2.15, P = 1.23 × 10−44) and DNase I hypersensitivity sites (DHSs) in CD14+ monocytes (q1/q0 = 1.41, P = 0.08). We observed the common variants affected the risk of SLE mostly through by regulating multiple immune system processes and immune response signaling. This study sheds light on several immune cells and responses, as well as the regulatory effect of common variants in the pathogenesis of SLE

Use of Traditional Chinese Medicine and Its Impact on Medical Cost among Urban Ischemic Stroke Inpatients in China: A National Cross-Sectional Study

Background. Traditional Chinese medicine (TCM) has long been widely adopted by the Chinese people and has been covered by China’s basic medical insurance schemes to treat ischemic stroke. Previous research has mainly highlighted the therapy effect of TCM on ischemic stroke patients. Some studies have demonstrated that employing TCM can reduce the medical burden on other diseases. But no research has explored whether using TCM could reduce inpatient medical cost for ischemic stroke in mainland China. The purpose of this study is to investigate the impact of the use of TCM on the total inpatient cost of ischemic stroke and to explore whether TCM has played the role of being complementary to, or an alternative for, conventional medicine to treat ischemic stroke. Methods. We conducted a national cross-sectional analysis based on a 5% random sample from claims data of China Urban Employee Basic Medical Insurance (UEBMI) and Urban Resident Basic Medical Insurance (URBMI) schemes in 2015. Mann–Whitney test was used to compare unadjusted total inpatient cost, conventional medication cost, and nonpharmacy cost estimates. Ordinary least square regression analysis was performed to compare demographics-adjusted total inpatient cost and to examine the association between TCM cost and conventional medication cost. Results. A total of 47321 urban inpatients diagnosed with ischemic stroke were identified in our study, with 92.6% (43843) of the patients using TCM in their inpatient treatment. Total inpatient cost for TCM users was significantly higher than TCM nonusers (USD 1217 versus USD 1036, P<0.001). Conventional medication cost was significantly lower for TCM users (USD 335 versus USD 436, P<0.001). The average cost of TCM per patient among TCM users was USD 289. Among TCM users, conventional medication costs were found to be positively associated with TCM cost after adjusting for confounding factors (Coef. = 0.144, P<0.001). Conclusion. Although the use of TCM reduced the cost of conventional medicine compared with TCM nonusers, TCM imposed an extra financial component on the total inpatient cost on TCM users. Our study suggests that TCM mainly played a complementary role to conventional medicine in ischemic stroke treatment in mainland China

Possible Luttinger liquid behavior of edge transport in monolayer transition metal dichalcogenide crystals.

In atomically-thin two-dimensional (2D) semiconductors, the nonuniformity in current flow due to its edge states may alter and even dictate the charge transport properties of the entire device. However, the influence of the edge states on electrical transport in 2D materials has not been sufficiently explored to date. Here, we systematically quantify the edge state contribution to electrical transport in monolayer MoS2/WSe2 field-effect transistors, revealing that the charge transport at low temperature is dominated by the edge conduction with the nonlinear behavior. The metallic edge states are revealed by scanning probe microscopy, scanning Kelvin probe force microscopy and first-principle calculations. Further analyses demonstrate that the edge-state dominated nonlinear transport shows a universal power-law scaling relationship with both temperature and bias voltage, which can be well explained by the 1D Luttinger liquid theory. These findings demonstrate the Luttinger liquid behavior in 2D materials and offer important insights into designing 2D electronics

Investigating the self-healing of dynamic covalent thermoset polyimine and its nanocomposites

Self-healable and recyclable materials and electronics can improve the reliability and repairability, and can reduce environmental pollution, therefore they promise very broad applications. In this study, we investigated the self-healing performance of dynamic covalent thermoset polyimine and its nanocomposites based on dynamic covalent chemistry. Heat press was applied to two laminating films of polyimine and its nanocomposites to induce self-healing. The effects of heat press time, temperature and load on the interfacial shear strength of re-healed films were investigated. The results showed that increasing the heat press time, temperature and load can significantly improve the interfacial shear strength and thus the self-healing effect. For polyimine nanocomposites, increasing the heat press time, temperature and load led to improved electrical conductivity of the re-healed films.</p