4,242 research outputs found
Measuring unified DM and DE properties with 3D cosmic shear
No full textWe investigate how 3D cosmic shear can constrain a class of cosmological models in which both the matter-dominated epoch of the evolution of the Universe and its current, accelerated expansion can be driven by a single, exotic scalar field with a non-canonical kinetic term in its Lagrangian, which behaves both as Dark Matter (DM) and Dark Energy (DE)
Comparison of 50° handheld fundus camera versus ultra-widefield table-top fundus camera for diabetic retinopathy detection and grading
Get PDFObjectivesTo compare the performance of a handheld fundus camera with standard 50 degrees visual field to ultra-widefield (UWF) table-top fundus camera in diabetic retinopathy (DR) detection and grading.MethodsPatients affected by diabetes mellitus and referred to our diabetic retinopathy clinic were enroled and underwent fundus photography in mydriasis. All photos were taken using the ultra-widefield table-top fundus camera Zeiss Clarus (TM) 500 (four fields per eye) and the Optomed Aurora (R) handheld fundus camera (3 fields per eye). The following parameters were analysed: the gradability of the images, the grade of DR, and diabetic maculopathy (DM), the presence of hypertensive retinopathy (HR) and the presence of other ocular diseases.ResultsWe enroled 759 eyes of 384 diabetic patients and analysed 5313 fundus photos. The handheld fundus camera obtained a sensitivity of 84.2% and specificity of 95.4% for referable cases. Moreover, it obtained, compared to UWF, an almost perfect agreement with linear weighting for DR, DM and HR (k = 0.877, k = 0.854, and k = 0.961, respectively). The lowest sensitivity was achieved for proliferative DR (58.7% sensitivity, 100% specificity).ConclusionsOptomed Aurora (R) handheld fundus camera imaging showed a strong agreement compared to UWF in grading DR, considering all DR and DM grades, in mydriasis. However, the use of UWF imaging increases the detection of referable eyes
Handheld Fundus Camera for Diabetic Retinopathy Screening: A Comparison Study with Table-Top Fundus Camera in Real-Life Setting
Get PDFThe aim of the study was to validate the performance of the Optomed Aurora(®) handheld fundus camera in diabetic retinopathy (DR) screening. Patients who were affected by diabetes mellitus and referred to the local DR screening service underwent fundus photography using a standard table-top fundus camera and the Optomed Aurora(®) handheld fundus camera. All photos were taken by a single, previously unexperienced operator. Among 423 enrolled eyes, we found a prevalence of 3.55% and 3.31% referable cases with the Aurora(®) and with the standard table-top fundus camera, respectively. The Aurora(®) obtained a sensitivity of 96.9% and a specificity of 94.8% in recognizing the presence of any degree of DR, a sensitivity of 100% and a specificity of 99.8% for any degree of diabetic maculopathy (DM) and a sensitivity of 100% and specificity of 99.8% for referable cases. The overall concordance coefficient k (95% CI) was 0.889 (0.828–0.949) and 0.831 (0.658–1.004) with linear weighting for DR and DM, respectively. The presence of hypertensive retinopathy (HR) was recognized by the Aurora(®) with a sensitivity and specificity of 100%. The Optomed Aurora(®) handheld fundus camera proved to be effective in recognizing referable cases in a real-life DR screening setting. It showed comparable results to a standard table-top fundus camera in DR, DM and HR detection and grading. The Aurora(®) can be integrated into telemedicine solutions and artificial intelligence services which, in addition to its portability and ease of use, make it particularly suitable for DR screening
DM-SLAM: Monocular SLAM in Dynamic Environments
No full textMany classic visual monocular SLAM (simultaneous localization and mapping) systems have been developed over the past decades, yet most of them fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM2. This article mainly concentrates on two aspects. Firstly, we proposed a distribution and local-based RANSAC (Random Sample Consensus) algorithm (DLRSAC) to extract static features from the dynamic scene based on awareness of the nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we designed a candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conducted experiments in the public dataset and compared DM-SLAM with ORB-SLAM2. The experiments corroborated the superiority of the DM-SLAM
Mathematical models for camera calibration and application to the PANCAM
No full textopenRecent years have seen an international growing interest in lunar exploration. In 2019, the European Space Agency (ESA) opened a campaign asking for innovative proposals aimed at the exploration, documentation and 3D mapping of lunar volcanic cavities. One of the selected projects was the DAEDALUS Sphere (Descent And Exploration in Deep Autonomy of Lava Underground Structures): a spherical robot which hosts four bifocal panoramic lenses, the so-called BLPs, and is able to perform an immersive stereoscopic map of lunar caves. Due to the strong optical anamorphism inherent to the PANCAM lens, which captures the panoramic field, it is necessary to utilize image dewarping algorithms. A preliminary yet crucial step in the dewarping process is camera calibration, which consists in computing the parameters of a camera. In this thesis we analyse mathematical models for camera calibration. We start with Zhang’s algorithm, which follows the simple pinhole projection model and then introduces lens distortion. In order to better describe very-wide angle cameras, we present the model and toolbox proposed by Scaramuzza. To test both the model and the software, we use the PANCAM to acquire some pictures of a checkerboard, which is the calibration pattern that allows to obtain the parameters of the camera. In particular, we try to understand if Scaramuzza’s model accurately describes the hyper-hemispheric part of the PANCAM lens.Recent years have seen an international growing interest in lunar exploration. In 2019, the European Space Agency (ESA) opened a campaign asking for innovative proposals aimed at the exploration, documentation and 3D mapping of lunar volcanic cavities. One of the selected projects was the DAEDALUS Sphere (Descent And Exploration in Deep Autonomy of Lava Underground Structures): a spherical robot which hosts four bifocal panoramic lenses, the so-called BLPs, and is able to perform an immersive stereoscopic map of lunar caves. Due to the strong optical anamorphism inherent to the PANCAM lens, which captures the panoramic field, it is necessary to utilize image dewarping algorithms. A preliminary yet crucial step in the dewarping process is camera calibration, which consists in computing the parameters of a camera. In this thesis we analyse mathematical models for camera calibration. We start with Zhang’s algorithm, which follows the simple pinhole projection model and then introduces lens distortion. In order to better describe very-wide angle cameras, we present the model and toolbox proposed by Scaramuzza. To test both the model and the software, we use the PANCAM to acquire some pictures of a checkerboard, which is the calibration pattern that allows to obtain the parameters of the camera. In particular, we try to understand if Scaramuzza’s model accurately describes the hyper-hemispheric part of the PANCAM lens
Entanglement and quantity in quantum space - About quantum measurement (II)
No full textAs a continuation and extension of "quantity in phase space" "quantity in quantum space" is introduced. With that, the disappearing of quantum interference discussed in a previous paper [S. Durr, et al., Nature 395 (1998) 33] is explained in the same spirit as our recent papers [Ren De-Ming, Commun. Theor. Phys. (Beijing, China) 41 (2004) 685, 833].Physics, MultidisciplinarySCI(E)中国科学引文数据库(CSCD)1ARTICLE133-364
Sneutrino DM in the NMSSM with inverse seesaw mechanism
No full textIn supersymmetric theories like the Next-to-Minimal Supersymmetric Standard Model (NMSSM), the lightest neutralino with bino or singlino as its dominant component is customarily taken as dark matter (DM) candidate. Since light Higgsinos favored by naturalness can strength the couplings of the DM and thus enhance the DM-nucleon scattering rate, the tension between naturalness and DM direct detection results becomes more and more acute with the improved experimental sensitivity. In this work, we extend the NMSSM by inverse seesaw mechanism to generate neutrino mass, and show that in certain parameter space the lightest sneutrino may act as a viable DM candidate, i.e. it can annihilate by multi-channels to get correct relic density and meanwhile satisfy all experimental constraints. The most striking feature of the extension is that the DM-nucleon scattering rate can be naturally below its current experimental bounds regardless of the higgsino mass, and hence it alleviates the tension between naturalness and DM experiments. Other interesting features include that the Higgs phenomenology becomes much richer than that of the original NMSSM due to the relaxed constraints from DM physics and also due to the presence of extra neutrinos, and that the signatures of sparticles at colliders are quite different from those with neutralino as DM candidate.National Natural Science Foundation of China (NNSFC) [11575053]SCI(E)ARTICLE1
Classical mechanics and quantum mechanics
No full textThe Newton equation of motion is derived from quantum mechanics.Physics, MultidisciplinarySCI(E)中国科学引文数据库(CSCD)2ARTICLE5685-6884
Performance of the Fast Atmospheric Self Coherent Camera at the NEW-EARTH Lab and a Simplified Measurement Algorithm
No full textIn order to detect low mass and mature planets inwards of approximately 5 AU, future direct imaging instruments will require precision wavefront control that operates at relatively high speed. The self-coherent camera (SCC) is a promising technique for measuring the wavefront from science images at the focal plane. We present here results from NRC’s NEW-EARTH lab testing of the Fast Atmospheric SCC Technique, a variant of the SCC and its integration with a Lyot-stop Low-Order Wavefront Sensor. We demonstrate correction of quasi-static speckles in a half dark hole reaching raw 1σ contrasts on the order of 5 × 10−7 at 10 λ/D. We also present a simplified process for extracting measurements and/or DM commands from SCC images using a single matrixvector multiply. This testing and development are important steps on the way to the upcoming Subaru Pathfinder Instrument for Detection of Exoplanets and Removal of Speckles and the Gemini Planet Imager’s CAL2 upgrade.We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), 466479467. This research used the facilities of the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. The authors are grateful to have performed this work on the traditional territories of the Coast Salish and Lekwungen-speaking peoples of Vancouver Island
A reality check for radiometric camera response recovery algorithms
No full textThe radiometric response of a camera governs the relationship between the incident light on the camera sensor and the output pixel values that are produced. This relationship, which is typically unknown and nonlinear, needs to be estimated for applications that require accurate measurement of scene radiance. Until now, various camera response recovery algorithms have been proposed each with different merits and drawbacks. However, an evaluation study that compares these algorithms has not been presented. In this work, we aim to fill this gap by conducting a rigorous experiment that evaluates the selected algorithms with respect to three metrics: consistency, accuracy, and robustness. In particular, we seek the answer of the following four questions: (1) Which camera response recovery algorithm gives the most accurate results? (2) Which algorithm produces the camera response most consistently for different scenes? (3) Which algorithm performs better under varying degrees of noise? (4) Does the sRGB assumption hold in practice? Our findings indicate that Grossberg and Nayar's (GN) algorithm (2004 [1]) is the most accurate; Mitsunaga and Nayar's (MN) algorithm (1999 [2]) is the most consistent; and Debevec and Malik's (DM) algorithm (1997 [3]) is the most resistant to noise together with MN. We also find that the studied algorithms are not statistically better than each other in terms of accuracy although all of them statistically outperform the sRGB assumption. By answering these questions, we aim to help the researchers and practitioners in the high dynamic range (HDR) imaging community to make better choices when choosing an algorithm for camera response recovery
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