LHDR: HDR Reconstruction for Legacy Content using a Lightweight DNN

High dynamic range (HDR) image is widely-used in graphics and photography due to the rich information it contains. Recently the community has started using deep neural network (DNN) to reconstruct standard dynamic range (SDR) images into HDR. Albeit the superiority of current DNN-based methods, their application scenario is still limited: (1) heavy model impedes real-time processing, and (2) inapplicable to legacy SDR content with more degradation types. Therefore, we propose a lightweight DNN-based method trained to tackle legacy SDR. For better design, we reform the problem modeling and emphasize degradation model. Experiments show that our method reached appealing performance with minimal computational cost compared with others.Comment: Accepted in ACCV202

Learning a Practical SDR-to-HDRTV Up-conversion using New Dataset and Degradation Models

In media industry, the demand of SDR-to-HDRTV up-conversion arises when users possess HDR-WCG (high dynamic range-wide color gamut) TVs while most off-the-shelf footage is still in SDR (standard dynamic range). The research community has started tackling this low-level vision task by learning-based approaches. When applied to real SDR, yet, current methods tend to produce dim and desaturated result, making nearly no improvement on viewing experience. Different from other network-oriented methods, we attribute such deficiency to training set (HDR-SDR pair). Consequently, we propose new HDRTV dataset (dubbed HDRTV4K) and new HDR-to-SDR degradation models. Then, it's used to train a luminance-segmented network (LSN) consisting of a global mapping trunk, and two Transformer branches on bright and dark luminance range. We also update assessment criteria by tailored metrics and subjective experiment. Finally, ablation studies are conducted to prove the effectiveness. Our work is available at: https://github.com/AndreGuo/HDRTVDM.Comment: Accepted by CVPR202

Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display

ITM(inverse tone-mapping) converts SDR (standard dynamic range) footage to HDR/WCG (high dynamic range /wide color gamut) for media production. It happens not only when remastering legacy SDR footage in front-end content provider, but also adapting on-theair SDR service on user-end HDR display. The latter requires more efficiency, thus the pre-calculated LUT (look-up table) has become a popular solution. Yet, conventional fixed LUT lacks adaptability, so we learn from research community and combine it with AI. Meanwhile, higher-bit-depth HDR/WCG requires larger LUT than SDR, so we consult traditional ITM for an efficiency-performance trade-off: We use 3 smaller LUTs, each has a non-uniform packing (precision) respectively denser in dark, middle and bright luma range. In this case, their results will have less error only in their own range, so we use a contribution map to combine their best parts to final result. With the guidance of this map, the elements (content) of 3 LUTs will also be redistributed during training. We conduct ablation studies to verify method's effectiveness, and subjective and objective experiments to show its practicability. Code is available at: https://github.com/AndreGuo/ITMLUT.Comment: Accepted in CVMP2023 (the 20th ACM SIGGRAPH European Conference on Visual Media Production

Addition of T2-Guided Optical Tomography Improves Noncontrast Breast Magnetic Resonance Imaging Diagnosis.

BACKGROUND: While dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is recognized as the most sensitive examination for breast cancer detection, it has a substantial false positive rate and gadolinium (Gd) contrast agents are not universally well tolerated. As a result, alternatives to diagnosing breast cancer based on endogenous contrast are of growing interest. In this study, endogenous near-infrared spectral tomography (NIRST) guided by T2 MRI was evaluated to explore whether the combined imaging modality, which does not require contrast injection or involve ionizing radiation, can achieve acceptable diagnostic performance. METHODS: Twenty-four subjects-16 with pathologically confirmed malignancy and 8 with benign abnormalities-were simultaneously imaged with MRI and NIRST prior to definitive pathological diagnosis. MRIs were evaluated independently by three breast radiologists blinded to the pathological results. Optical image reconstructions were constrained by grayscale values in the T2 MRI. MRI and NIRST images were used, alone and in combination, to estimate the diagnostic performance of the data. Outcomes were compared to DCE results. RESULTS: Sensitivity, specificity, accuracy, and area under the curve (AUC) of noncontrast MRI when combined with T2-guided NIRST were 94%, 100%, 96%, and 0.95, respectively, whereas these values were 94%, 63%, 88%, and 0.81 for DCE MRI alone, and 88%, 88%, 88%, and 0.94 when DCE-guided NIRST was added. CONCLUSION: In this study, the overall accuracy of imaging diagnosis improved to 96% when T2-guided NIRST was added to noncontrast MRI alone, relative to 88% for DCE MRI, suggesting that similar or better diagnostic accuracy can be achieved without requiring a contrast agent

Association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of type 2 diabetes mellitus among Chinese elderly: The Beijing Longitudinal Study of Aging

Objective: Time-dependent covariates are generally available as longitudinal data were collected periodically in the cohort study. To examine whether time-dependent triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio could predict the future risk of type 2 diabetes mellitus (T2DM) and assess its potential impact on the risk of T2DM incidence. Research design and methods: This study enrolled 1460 participants without T2DM aged 55 or above in 1992 in the Beijing Longitudinal Study of Aging during 25 years. The questionnaire data were collected in nine surveys from 1992 to 2017. Physical examination and blood laboratory tests including TG and HDL-C concentrations were measured in five surveys. Incident T2DM cases were confirmed via a self-reported history of T2DM or the fasting plasma glucose level. Results: 119 new cases of T2DM were identified. In the Cox regression analysis with time-dependent TG/HDL-C ratios and covariates, the adjusted hazard ratios (95% confidence interval) of T2DM incidence were 1.90 (1.12 to 3.23), 2.75 (1.58 to 4.80) and 2.84 (1.69 to 4.77), respectively, for those with TG/HDL-C ratios (both TG and HDL-C were expressed in millimole per liter) in the ranges of 0.87-1.30, 1.31-1.74 and ≥ 1.75, compared with individuals with TG/HDL-C ratios \u3c 0.87. The similar results of subdistribution hazard ratios were obtained by performing the Fine-Gray model with time-dependent TG/HDL-C ratios. This positive association and the statistically significant trend with increased risk of T2DM incidence in the three categories of elevated TG/HDL-C ratio was confirmed by multiple sensitivity analyses. Furthermore, the T2DM discriminatory power of TG/HDL-C ratio combining with other risk factors was moderately high. Conclusions: We found that time-dependent TG/HDL-C ratios were positively associated with the risk of T2DM risk. The elevated TG/HDL-C ratios increased the future risk of T2DM incidence. Lowering the TG/HDL-C ratio could assist in the prevention of diabetes for older adults. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ

Association of impaired sensitivity to thyroid hormones with hyperuricemia through obesity in the euthyroid population

Background: Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. Methods: This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008–2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. Results: Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04–1.35; PTFQI: OR = 1.20, 95% CI 1.05–1.36; TT4RI: OR = 1.17, 95% CI 1.08–1.27; TSHI: OR = 1.12, 95% CI 1.04–1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. Conclusions: Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity

On the role of horizontal resolution over the Tibetan Plateau in the REMO regional climate model

A number of studies have shown that added value is obtained by increasing the horizontal resolution of a regional climate model to capture additional fine-scale weather processes. However, the mechanisms leading to this added value are different over areas with complicated orographic features, such as the Tibetan Plateau (TP). To determine the role that horizontal resolution plays over the TP, a detailed comparison was made between the results from the REMO regional climate model at resolutions of 25 and 50 km for the period 1980–2007. The model was driven at the lateral boundaries by the European Centre for Medium-Range Weather Forecasts Interim Reanalysis data. The experiments differ only in representation of topography, all other land parameters (e.g., vegetation characteristics, soil texture) are the same. The results show that the high-resolution topography affects the regional air circulation near the ground surface around the edge of the TP, which leads to a redistribution of the transport of atmospheric water vapor, especially over the Brahmaputra and Irrawaddy valleys—the main water vapor paths for the southern TP—increasing the amount of atmospheric water vapor transported onto the TP by about 5. This, in turn, significantly decreases the temperature at 2 m by > 1.5 °C in winter in the high-resolution simulation of the southern TP. The impact of topography on the 2 m temperature over the TP is therefore by influencing the transport of atmospheric water vapor in the main water vapor paths. © 2018 Springer-Verlag GmbH Germany, part of Springer Natur

Combined evaluation of arterial stiffness and blood pressure promotes risk stratification of peripheral arterial disease

Background: Previous studies have reported the separate association of arterial stiffness (AS) and blood pressure with peripheral arterial disease (PAD). Objectives: The aim of this study was to investigate the risk stratification capacity of AS on incident PAD beyond blood pressure status. Methods: A total of 8,960 participants from Beijing Health Management Cohort were enrolled at the first health visit between 2008 and 2018 and then followed until the incidence of PAD or 2019. Elevated AS was defined as brachial-ankle pulse-wave velocity (baPWV) \u3e 1,400 cm/s, including moderate stiffness (1,400 ≤ baPWV \u3c 1,800 cm/s) and severe stiffness (baPWV ≥ 1,800 cm/s). PAD was defined as ankle-brachial index \u3c 0.9. A frailty Cox model was used to calculate the HR, integrated discrimination improvement, and net reclassification improvement. Results: During follow-up, 225 participants (2.5%) developed PAD. After adjusting for confounding factors, the highest risk for PAD was observed in the group with elevated AS and blood pressure (HR: 2.253; 95% CI: 1.472-3.448). Among participants with ideal blood pressure and those with well-controlled hypertension, PAD risk was still significant for severe AS. The results remained consistent in multiple sensitivity analyses. In addition, baPWV significantly improved the predictive capacity for PAD risk beyond systolic and diastolic blood pressures (integrated discrimination improvement 0.020 and 0.190, net reclassification improvement 0.037 and 0.303). Conclusions: This study suggests the clinical importance of combined evaluation and control of AS and blood pressure for the risk stratification and prevention of PAD