583 research outputs found

    Segmentation-aware Image Denoising Without Knowing True Segmentation

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    Recent works have discussed application-driven image restoration neural networks capable of not only removing noise in images but also preserving their semantic-aware details, making them suitable for various high-level computer vision tasks as the pre-processing step. However, such approaches require extra annotations for their high-level vision tasks in order to train the joint pipeline using hybrid losses, yet the availability of those annotations is often limited to a few image sets, thereby restricting the general applicability of these methods to simply denoise more unseen and unannotated images. Motivated by this, we propose a segmentation-aware image denoising model dubbed U-SAID, based on a novel unsupervised approach with a pixel-wise uncertainty loss. U-SAID does not require any ground-truth segmentation map, and thus can be applied to any image dataset. It is capable of generating denoised images with comparable or even better quality than that of its supervised counterpart and even more general “application-agnostic” denoisers, and its denoised results show stronger robustness for subsequent semantic segmentation tasks. Moreover, plugging its “universal” denoiser without fine-tuning, we demonstrate the superior generalizability of U-SAID in three-folds: (1) denoising unseen types of images; (2) denoising as preprocessing for segmenting unseen noisy images; and (3) denoising for unseen high-level tasks. Extensive experiments were conducted to assess the effectiveness and robustness of the proposed U-SAID model against various popular image sets

    ELM of ELM-WD: An extremely low mass hot donor star discovered in LAMOST survey

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    The Extremely Low Mass White Dwarfs (ELM WDs) and pre-ELM WDs are helium core white dwarfs with mass <0.3M<\sim 0.3M_{\odot}. They are formed in close binaries and have lost over half of their initial masses via Common Envelope (CE) ejection or stable Roche Lobe Over Flow (RLOF). Both evolution simulations and observations show that a lower mass limit for ELM WDs exists at 0.14M\approx0.14M_{\odot}. Here we report the discovery of an extremely low mass ELM WD, ID70904216 in LAMOST survey, that may be lower than the ELM WD mass limit. Based on LAMOST and P200 spectroscopic observations, ID70904216 shows orbital period Porb=P_{orb} = 0.219658 days and radial velocity semi-amplitude K1=317.33km/sK1=317.33km/s, which gives the mass function of 0.73MM_{\odot}, indicating the companion is a compact star. The low resolution spectra shows a F type star with Teff7361KT_{\rm eff} \sim 7361K without emission features. The temperature is consistent with that derived from SED fitting(7440K7440K) and multi-color light curve solution(7400K7400K). The optical light curves, in ZTF g, r and i bands and Catalina V band, show ellipsoidal variability with amplitudes 30%\approx30\%, suggesting that the visible companion is heavily tidal distorted. Combining with the distance from Gaia survey, the WD code modeling estimates that the mass of the visible star is M1=0.080.03+0.06MM1=0.08^{+0.06}_{-0.03}M_{\odot}, and the mass of the invisible star is M2=0.940.10+0.45MM2=0.94^{+0.45}_{-0.10}M_{\odot}. The radius of the visible donor is R=0.29±0.01RR=0.29\pm0.01R_{\odot}. The inclination angle is constrained between 60^{\circ} and 90^{\circ}. The observations indicate the system is a pre-ELM WD + WD/NS binary system with an extremely low mass hot donor below the 0.14M0.14M_{\odot} theoretical limit.Comment: 16 pages, 10 figure

    Baseline microglial activation correlates with brain amyloidosis and longitudinal cognitive decline in Alzheimer disease

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    BACKGROUND AND OBJECTIVES: This study aims to quantify microglial activation in individuals with Alzheimer disease (AD) using the 18-kDa translocator protein (TSPO) PET imaging in the hippocampus and precuneus, the 2 AD-vulnerable regions, and to evaluate the association of baseline neuroinflammation with amyloidosis, tau, and longitudinal cognitive decline. METHODS: Twenty-four participants from the Knight Alzheimer Disease Research Center (Knight ADRC) were enrolled and classified into stable cognitively normal, progressor, and symptomatic AD groups based on clinical dementia rating (CDR) at 2 or more clinical assessments. The baseline TSPO radiotracer [11C]PK11195 was used to image microglial activation. Baseline CSF concentrations of Aβ42, Aβ42/Aβ40 ratio, tau phosphorylated at position 181 (p-tau181), and total tau (t-tau) were measured. Clinical and cognitive decline were examined with longitudinal CDR and cognitive composite scores (Global and Knight ADRC-Preclinical Alzheimer Cognitive Composite [Knight ADRC-PACC] Score). RESULTS: Participants in the progressor and symptomatic AD groups had significantly elevated [11C]PK11195 standard uptake value ratios (SUVRs) in the hippocampus but not in the precuneus region. In the subcohort with CSF biomarkers (16 of the 24), significant negative correlations between CSF Aβ42 or Aβ42/Aβ40 and [11C]PK11195 SUVR were observed in the hippocampus and precuneus. No correlations were observed between [11C]PK11195 SUVR and CSF p-tau181 or t-tau at baseline in those regions. Higher baseline [11C]PK11195 SUVR averaged in the whole cortical regions predicted longitudinal decline on cognitive tests. DISCUSSION: Microglial activation is increased in individuals with brain amyloidosis and predicts worsening cognition in AD. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with AD, higher baseline [11C]PK11195 SUVR averaged in the whole cortical regions was associated with longitudinal decline on cognitive tests
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