Adaptive automated sinogram normalization for ring artifacts suppression in CT.

Ring artifacts pose a major barrier to obtaining precise reconstruction in computed tomography (CT). The presence of ring artifacts complicates the use of automatic means of processing CT reconstruction results, such as segmentation, correction of geometric shapes, alignment of reconstructed volumes. Although there are numerous efficient methods for suppressing ring artifacts, many of them appear to be manual. Along with this, a large proportion of the automatic methods cope unsatisfactorily with the target task while requiring computational capacity. The current work introduces a projection data preprocessing method for suppressing ring artifacts that constitutes a compromise among the outlined aspects - automaticity, high efficiency and computational speed. Derived as the automation of the classical sinogram normalization method, the proposed method specific advantages consist in adaptability in relation to the filtered sinograms and the edge-preservation property proven within the experiments on both synthetic and real CT data. Concerning the challenging open-access data, the method has performed superior quality comparable to that of the advanced methods: it has demonstrated 70.4% ring artifacts suppression percentage (RASP) quality metric. In application to our real laboratory CT data, the proposed method allowed us to gain significant refinement of the reconstruction quality which has not been surpassed by a range of compared manual ring artifacts suppression methods.

Reducing radiation dose for NN-based COVID-19 detection in helical chest CT using real-time monitored reconstruction.

Computed tomography is a powerful tool for medical examination, which plays a particularly important role in the investigation of acute diseases, such as COVID-19. A growing concern in relation to CT scans is the radiation to which the patients are exposed, and a lot of research is dedicated to methods and approaches to how to reduce the radiation dose in X-ray CT studies. In this paper, we propose a novel scanning protocol based on real-time monitored reconstruction for a helical chest CT using a pre-trained neural network model for COVID-19 detection as an expert. In a simulated study, for the first time, we proposed using per-slice stopping rules based on the COVID-19 detection neural network output to reduce the frequency of projection acquisition for portions of the scanning process. The proposed method allows reducing the total number of X-ray projections necessary for COVID-19 detection, and thus reducing the radiation dose, without a significant decrease in the prediction accuracy. The proposed protocol was evaluated on 163 patients from the COVID-CTset dataset, providing a mean dose reduction of 15.1% while the mean decrease in prediction accuracy amounted to only 1.9% achieving a Pareto improvement over a fixed protocol.

Deep Learning-Based Segmentation of Post-Mortem Human's Olfactory Bulb Structures in X-ray Phase-Contrast Tomography.

The human olfactory bulb (OB) has a laminar structure. The segregation of cell populations in the OB image poses a significant challenge because of indistinct boundaries of the layers. Standard 3D visualization tools usually have a low resolution and cannot provide the high accuracy required for morphometric analysis. X-ray phase contrast tomography (XPCT) offers sufficient resolution and contrast to identify single cells in large volumes of the brain. The numerous microanatomical structures detectable in XPCT image of the OB, however, greatly complicate the manual delineation of OB neuronal cell layers. To address the challenging problem of fully automated segmentation of XPCT images of human OB morphological layers, we propose a new pipeline for tomographic data processing. Convolutional neural networks (CNN) were used to segment XPCT image of native unstained human OB. Virtual segmentation of the whole OB and an accurate delineation of each layer in a healthy non-demented OB is mandatory as the first step for assessing OB morphological changes in smell impairment research. In this framework, we proposed an effective tool that could help to shed light on OB layer-specific degeneration in patients with olfactory disorder.

Document Liveness Challenge Dataset (DLC-2021).

Various government and commercial services, including, but not limited to, e-government, fintech, banking, and sharing economy services, widely use smartphones to simplify service access and user authorization. Many organizations involved in these areas use identity document analysis systems in order to improve user personal-data-input processes. The tasks of such systems are not only ID document data recognition and extraction but also fraud prevention by detecting document forgery or by checking whether the document is genuine. Modern systems of this kind are often expected to operate in unconstrained environments. A significant amount of research has been published on the topic of mobile ID document analysis, but the main difficulty for such research is the lack of public datasets due to the fact that the subject is protected by security requirements. In this paper, we present the DLC-2021 dataset, which consists of 1424 video clips captured in a wide range of real-world conditions, focused on tasks relating to ID document forensics. The novelty of the dataset is that it contains shots from video with color laminated mock ID documents, color unlaminated copies, grayscale unlaminated copies, and screen recaptures of the documents. The proposed dataset complies with the GDPR because it contains images of synthetic IDs with generated owner photos and artificial personal information. For the presented dataset, benchmark baselines are provided for tasks such as screen recapture detection and glare detection. The data presented are openly available in Zenodo.

On the properties of some low-parameter models for color reproduction in terms of spectrum transformations and coverage of a color triangle.

One of the classical approaches to solving color reproduction problems, such as color adaptation or color space transform, is the use of a low-parameter spectral model. The strength of this approach is the ability to choose a set of properties that the model should have, be it a complete coverage of a color triangle or an accurate description of the addition or multiplication of spectra, knowing only the tristimulus corresponding to them. The disadvantage is that some of the properties of the mentioned spectral models are confirmed only experimentally. This work is devoted to the theoretical substantiation of various properties of spectral models. In particular, we prove that the banded model is the only model that simultaneously possesses the properties of closure under addition and multiplication. We also show that the Gaussian model is the limiting case of the von Mises model and prove that the von Mises model unambiguously covers the color triangle in cases of both convex and non-convex spectral loci.

Analysis of Video Game Players' Emotions and Team Performance: An Esports Tournament Case Study.

Video gaming and eSports is a quickly developing industry already involving billions of players worldwide. Gaming and eSports tournaments require strong mental abilities to avoid severe stress and other negative consequences upon completing the game. In this article, we report on the impact of emotions on a team performance. For this reason, we collect audio recordings and game logs from the players in real conditions at an eSports tournament. This data is further used in trained machine learning models for analysis of players' emotional conditions from the voice during the game. We considered recognition of several types of emotions as well as the background sounds. To do this, we trained 92.7% accuracy classifier of six most common classes of emotions and sounds in eSports audio and applied it to eSports data. As a result, we demonstrate that there is an opportunity to measure the eSports team's performance from the players' emotional conditions obtained from the voice communication. We found that there is a strong correlation among the performance of the team, communication between the players, and emotional sentiment of communication. The teams achieve much better results when they had much more internal conversations during the game.

Holographic extraction of plane waves from an ultrasound beam for acoustic characterization of an absorbing layer of finite dimensions.

For the acoustic characterization of materials, a method is proposed for interpreting experiments with finite-sized transducers and test samples in terms of the idealized situation in which plane waves are transmitted through an infinite plane-parallel layer. The method uses acoustic holography, which experimentally provides complete knowledge of the wave field by recording pressure waveforms at points on a surface intersected by the acoustic beam. The measured hologram makes it possible to calculate the angular spectrum of the beam to decompose the field into a superposition of plane waves propagating in different directions. Because these waves cancel one another outside the beam, the idealized geometry of an infinite layer can be represented by a sample of finite size if its lateral dimensions exceed the width of the acoustic beam. The proposed method relies on holograms that represent the acoustic beam with and without the test sample in the transmission path. The method is described theoretically, and its capabilities are demonstrated experimentally for silicone rubber samples by measuring their frequency-dependent phase velocities and absorption coefficients in the megahertz frequency range.

Enhanced Tomographic Sensing Multimodality with a Crystal Analyzer.

This article demonstrates how a combination of well-known tools-a standard 2D detector (CCD (charge-coupled device) camera) and a crystal analyzer-can improve the multimodality of X-ray imaging and tomographic sensing. The use of a crystal analyzer allowed two characteristic lines of the molybdenum anode-Kα and Kß-to be separated from the polychromatic radiation of the conventional X-ray tube. Thus, as a result of one measurement, three radiographic projections (images) were simultaneously recorded. The projection images at different wavelengths were separated in space and registered independently for further processing, which is of interest for the spectral tomography method. A projective transformation to compensate for the geometric distortions that occur during asymmetric diffraction was used. The first experimental results presented here appear promising.

Monitoring of body fluid redistribution using segmental bioimpedance during rotation on a short-radius centrifuge.

OBJECTIVE: The creation of artificial gravity on board a space station is one of the promising methods for preventing health problems during space missions; a short-radius centrifuge (SRC) is the model of such a method on Earth. Our goal was to evaluate the sensitivity of bioimpedance polysegmental measurements for monitoring of the body regions' blood-filling redistribution and to analyze the dynamics of blood-filling redistribution during rotation in three SRC rotation modes. APPROACH: Nine healthy male volunteers have been observed under three SRC rotation modes with a maximum acceleration of 2.05 standard Earth gravity (g), 2.47 g, 2.98 g along the body vertical axis towards the legs with a rotation radius of 235 cm. The 5 kHz electrical resistance was evaluated using a bioimpedance analyzer in a polysegmental mode. MAIN RESULTS: Twenty-five correct records were made, of which four records were incomplete since the tests had to be stopped because the subjects were not feeling well. There was a blood-filling decrease in the head region; resistance increased to +15.4% ± 4.1% in the first SRC rotation mode. The electrical resistance of the leg regions decreased to -16.5% ± 2.3%. Slowdown of the SRC led to the reverse changes in resistance. The blood redistribution in the head and leg regions was independent of the mode of SRC rotation during the first 30 min, and varied on average by +10% and -15% respectively. SIGNIFICANCE: Bioimpedance monitoring is promising for detection and prediction of blood circulation changes during rotation on the SRC.

UAV Control on the Basis of 3D Landmark Bearing-Only Observations.

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.

Smooth Pursuit in Elderly Adults Studied With Apparent Motion.

The variability of smooth pursuit eye movements was studied in a group of healthy subjects for horizontal apparent motion by a method that does not require direct measurements of eye movements. It was found that the individual smooth pursuit efficiencies for binocular perception in group of healthy elderly subjects (mean age 61 years) as well as in the group of healthy young adults were distinctly differentiated. Furthermore, we have not detected any age-related decrease in the fraction of subjects showing high smooth pursuit efficiencies. This fact demonstrates that the human oculomotor system is relatively resistant to the effects of aging. At the same time, an appreciable increase of percentage of persons with directional asymmetry of smooth pursuit has been found among elderly adults. A higher smooth pursuit efficiency was noticed reliably more often in the direction from left to right rather than in the opposite direction. Subject eye movements were recorded with i-View XTM Hi-Speed 1250 eye tracking system (SMI Inc.). These records confirmed that the smooth pursuit accuracy of older adults is less than that of young persons, at least in some directions of tracking.

Monochromatic computed microtomography using laboratory and synchrotron sources and X-ray fluorescence analysis for comprehensive analysis of structural changes in bones.

A combination of X-ray tomography at different wavelengths and X-ray fluorescence analysis was applied in the study of two types of bone tissue changes: prolonged presence in microgravity conditions and age-related bone growth. The proximal tail vertebrae of geckos were selected for investigation because they do not bear the supporting load in locomotion, which allows them to be considered as an independent indicator of gravitational influence. For the vertebrae of geckos no significant differences were revealed in the elemental composition of the flight samples and the synchronous control samples. In addition, the gecko bone tissue samples from the jaw apparatus, spine and shoulder girdle were measured. The dynamics of structural changes in the bone tissue growth was studied using samples of a human fetal hand. The hands of human fetuses of 11-15 weeks were studied. Autonomous zones of calcium accumulation were found not only in individual fingers but in each of the investigated phalanges. The results obtained are discussed.

Computed microtomography and X-ray fluorescence analysis for comprehensive analysis of structural changes in bone.

This paper presents the results of a comprehensive analysis of structural changes in the caudal vertebrae of Turner's thick-toed geckos by computer microtomography and X-ray fluorescence analysis. We present algorithms used for the reconstruction of tomographic images which allow to work with high noise level projections that represent typical conditions dictated by the nature of the samples. Reptiles, due to their ruggedness, small size, belonging to the amniote and a number of other valuable features, are an attractive model object for long-orbital experiments on unmanned spacecraft. Issues of possible changes in their bone tissue under the influence of spaceflight are the subject of discussions between biologists from different laboratories around the world.

Evaluation of nutritional screening tools among patients scheduled for heart valve surgery.

BACKGROUND AND AIM OF THE STUDY: The study aim was to detect the most sensitive nutritional screening tool and to assess its prognostic value with regards to an adverse clinical course in patients with heart valve disease undergoing cardiopulmonary bypass (CPB). METHODS: This prospective cohort study included 441 adult patients who were screened using four nutritional screening tools: Nutritional Risk Screening 2002 (NRS-2002); Malnutrition Universal Screening Tool (MUST); Mini Nutritional Assessment (MNA); and Short Nutritional Assessment Questionnaire (SNAQ). Nutritional assessment was performed using a Subjective Global Assessment (SGA). In-hospital mortality, postoperative complications, and duration of hospital stay were each analyzed. RESULTS: With regards to the detection of malnutrition, the sensitivities of MUST, SNAQ, MNA and NRS-2002 were 100%, 92%, 84.6% and 43.6%, respectively. Malnutrition identified by MUST and MNA were associated with postoperative complications (OR 1.63, p = 0.033 and OR 1.6, p = 0.035) and prolonged hospitalization (OR 1.57, p = 0.048 and OR 1.7, p = 0.02). According to multivariate logistic regression analysis, along with well-known age and duration of CPB, malnutrition identified by MUST and MNA was associated with a risk of development of complications (OR 1.6, p = 0.049 and OR 1.6, p = 0.04, respectively). The sensitivities of SNAQ, MUST, NRS-2002 and MNA with regards to postoperative complications were 26.8%, 28.8%, 10%, and 31.6%, respectively. CONCLUSION: The MUST tool is preferable with regards to the detection of malnutrition. Both, MUST and MNA independently predicted postoperative complications. SNAQ and NRS-2002 proved insensitive with regards to the postoperative course among patients with heart valve disease who were scheduled for cardiothoracic surgery.

Prognostic value of nutritional screening tools for patients scheduled for cardiac surgery.

OBJECTIVES: The aim of this study was to assess the prognostic value of different nutritional screening tools in patients undergoing cardiopulmonary bypass, with regard to adverse clinical outcome. METHODS: This prospective cohort study analysed 1193 adult patients who underwent cardiopulmonary bypass. Patients were screened using five nutritional screening tools: Subjective Global Assessment (SGA), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), Mini-Nutritional Assessment (MNA) and Short Nutritional Assessment Questionnaire (SNAQ). In-hospital mortality, postoperative complications, length of stay in intensive care unit and length of hospitalization were analysed. Multivariate backward logistic regression analysis was used to assess the independent predictive value of the studied screening tools. RESULTS: In accordance with univariate analysis, malnutrition detected by SNAQ, MUST, NRS-2002 and MNA was associated with postoperative complications (odds ratio [OR] 1.8, 95% confidence interval [95% CI] 1.3-2.4; OR 1.9, 95% CI 1.4-2.6; OR 1.8, 95% CI 1.2-2.9 and OR 1.9, 95% CI 1.4-2.6). Malnutrition detected by MUST, NRS-2002, MNA and SGA was associated with intensive care unit stay >2 days (OR 1.5, 95% CI 1.1-2.1; OR 2.3, 95% CI 1.5-3.7; OR 1.7, 95% CI 1.2-2.2 and OR 2.7, 95% CI 1.6-4.6). Prolonged hospitalization (>20 days) was predicted by SNAQ, MUST and MNA (OR 1.4, 95% CI 1-1.9; OR 1.6, 95% CI 1.2-2.2 and OR 1.6, 95% CI 1.2-2.2). In accordance with multivariate analysis, only MUST and MNA independently predicted postoperative complications (OR 1.6, 95% CI 1.1-2.3 and OR 1.6, 95% CI 1.1-2.2). Other independent factors influencing postoperative complications were well-known logistic EuroSCORE (OR 1.06, 95% CI 1-1.1) and the duration of cardiopulmonary bypass in minutes (OR 1.01, 95% CI 1-1.01). CONCLUSIONS: MUST and MNA both have independent predictive values with regard to postoperative complications. Taking into account simplicity, MUST is preferable for the cardiac surgical population.

Evaluation of nutritional screening tools for patients scheduled for cardiac surgery.

OBJECTIVE: The aim of this study was to assess the prognostic value of different nutritional screening tools in patients undergoing cardiopulmonary bypass with regard to an adverse clinical course. METHODS: This prospective cohort study analyzed 894 adult patients who underwent cardiopulmonary bypass. Patients were screened using four nutritional screening tools: Nutritional Risk Screening 2002 (NRS-2002), the Malnutrition Universal Screening Tool (MUST), the Mini-Nutritional Assessment (MNA), and the Short Nutritional Assessment Questionnaire (SNAQ). Nutritional status was assessed using the Subjective Global Assessment. In-hospital mortality, postoperative complications, length of stay in the intensive care unit, and length of hospitalization were analyzed. RESULTS: The sensitivities of the SNAQ, MUST, and NRS-2002 to detect the malnutrition confirmed by the Subjective Global Assessment were 91.5%, 97.9%, and 38.3%, respectively, and the MNA showed a sensitivity of 81.8% for the elderly. Malnutrition detected by the SNAQ, MUST, and NRS-2002 was associated with postoperative complications (odds ratios [ORs] 1.75, 1.98, and 1.82, respectively) and a stay in the intensive care unit longer than 2 d (ORs 1.46, 1.56, and 2.8). Malnutrition as detected by the SNAQ and MUST was also associated with prolonged hospitalization (ORs 1.49 and 1.59). According to multivariate logistic regression analysis, postoperative complications were independently predicted by the European System for Cardiac Operative Risk Evaluation (OR 1.1, P < 0.0001), cardiopulmonary bypass time (OR 1.01, P < 0.0001), and malnutrition identified by the MUST (OR 1.2, P = 0.01). CONCLUSION: The MUST independently predicts postoperative complications. The SNAQ and MUST have comparable accuracy in detecting malnutrition. Whether preoperative nutritional therapy would improve the outcome in malnourished patients needs to be studied.

Efficient and effective regularised ART for computed tomography.

Algebraic Reconstruction Technique (ART) is a widely employed method in computed tomography since it has certain advantages, such as allowing reconstruction of data with missing projections in some angle ranges, over other techniques such as Filtered Back Projection (FBP). Recently, a regularisation technique for ART, RegART, was introduced which provides greatly reduced noise levels. However, a serious drawback of both ART and RegART is the computational complexity of the methods. In this paper, we present a fast version of RegART, which makes use of nVidia's CUDA technology, and show that this approach performs favourably compared to FBP.