scholarly journals The probability distribution of 3D shapes of galaxy clusters from 2D X-ray images

2021 ◽  
Vol 503 (2) ◽  
pp. 2791-2803
Author(s):  
Swapnil Shankar ◽  
Rishi Khatri
Keyword(s):  
Probability Distribution ◽  
Galaxy Clusters ◽  
Galaxy Cluster ◽  
Data Sets ◽  
X Rays ◽  
Data Set ◽  
X Ray ◽  
Individual Object ◽  
3D Shape ◽  
3D Shapes

ABSTRACT We present a new method to determine the probability distribution of the 3D shapes of galaxy clusters from the 2D images using stereology. In contrast to the conventional approach of combining different data sets (such as X-rays, Sunyaev–Zeldovich effect, and lensing) to fit a 3D model of a galaxy cluster for each cluster, our method requires only a single data set, such as X-ray observations or Sunyaev–Zeldovich effect observations, consisting of sufficiently large number of clusters. Instead of reconstructing the 3D shape of an individual object, we recover the probability distribution function (PDF) of the 3D shapes of the observed galaxy clusters. The shape PDF is the relevant statistical quantity, which can be compared with the theory and used to test the cosmological models. We apply this method to publicly available Chandra X-ray data of 89 well-resolved galaxy clusters. Assuming ellipsoidal shapes, we find that our sample of galaxy clusters is a mixture of prolate and oblate shapes, with a preference for oblateness with the most probable ratio of principle axes 1.4 : 1.3 : 1. The ellipsoidal assumption is not essential to our approach and our method is directly applicable to non-ellipsoidal shapes. Our method is insensitive to the radial density and temperature profiles of the cluster. Our method is sensitive to the changes in shape of the X-ray emitting gas from inner to outer regions and we find evidence for variation in the 3D shape of the X-ray emitting gas with distance from the centre.

scholarly journals Probing cosmic isotropy with a new X-ray galaxy cluster sample through the LX–T scaling relation

2020 ◽  
Vol 636 ◽  
pp. A15 ◽  
Author(s):  
K. Migkas ◽  
G. Schellenberger ◽  
T. H. Reiprich ◽  
F. Pacaud ◽  
M. E. Ramos-Ceja ◽  
...  
Keyword(s):  
Galaxy Clusters ◽  
Statistical Significance ◽  
Cosmological Parameters ◽  
Galaxy Cluster ◽  
Temperature Measurements ◽  
Joint Analysis ◽  
Scaling Relations ◽  
Exact Nature ◽  
X Rays ◽  
X Ray

The isotropy of the late Universe and consequently of the X-ray galaxy cluster scaling relations is an assumption greatly used in astronomy. However, within the last decade, many studies have reported deviations from isotropy when using various cosmological probes; a definitive conclusion has yet to be made. New, effective and independent methods to robustly test the cosmic isotropy are of crucial importance. In this work, we use such a method. Specifically, we investigate the directional behavior of the X-ray luminosity-temperature (LX–T) relation of galaxy clusters. A tight correlation is known to exist between the luminosity and temperature of the X-ray-emitting intracluster medium of galaxy clusters. While the measured luminosity depends on the underlying cosmology through the luminosity distance DL, the temperature can be determined without any cosmological assumptions. By exploiting this property and the homogeneous sky coverage of X-ray galaxy cluster samples, one can effectively test the isotropy of cosmological parameters over the full extragalactic sky, which is perfectly mirrored in the behavior of the normalization A of the LX–T relation. To do so, we used 313 homogeneously selected X-ray galaxy clusters from the Meta-Catalogue of X-ray detected Clusters of galaxies. We thoroughly performed additional cleaning in the measured parameters and obtain core-excised temperature measurements for all of the 313 clusters. The behavior of the LX–T relation heavily depends on the direction of the sky, which is consistent with previous studies. Strong anisotropies are detected at a ≳4σ confidence level toward the Galactic coordinates (l, b) ∼ (280°, − 20°), which is roughly consistent with the results of other probes, such as Supernovae Ia. Several effects that could potentially explain these strong anisotropies were examined. Such effects are, for example, the X-ray absorption treatment, the effect of galaxy groups and low redshift clusters, core metallicities, and apparent correlations with other cluster properties, but none is able to explain the obtained results. Analyzing 105 bootstrap realizations confirms the large statistical significance of the anisotropic behavior of this sky region. Interestingly, the two cluster samples previously used in the literature for this test appear to have a similar behavior throughout the sky, while being fully independent of each other and of our sample. Combining all three samples results in 842 different galaxy clusters with luminosity and temperature measurements. Performing a joint analysis, the final anisotropy is further intensified (∼5σ), toward (l, b) ∼ (303°, − 27°), which is in very good agreement with other cosmological probes. The maximum variation of DL seems to be ∼16 ± 3% for different regions in the sky. This result demonstrates that X-ray studies that assume perfect isotropy in the properties of galaxy clusters and their scaling relations can produce strongly biased results whether the underlying reason is cosmological or related to X-rays. The identification of the exact nature of these anisotropies is therefore crucial for any statistical cluster physics or cosmology study.

scholarly journals COVID-Transformer: Interpretable COVID-19 Detection Using Vision Transformer for Healthcare

2021 ◽  
Vol 18 (21) ◽  
pp. 11086
Author(s):  
Debaditya Shome ◽  
T. Kar ◽  
Sachi Nandan Mohanty ◽  
Prayag Tiwari ◽  
Khan Muhammad ◽  
...  
Keyword(s):  
Data Science ◽  
Disease Spread ◽  
Classification Task ◽  
Data Sets ◽  
Sudden Increase ◽  
X Rays ◽  
Data Set ◽  
X Ray ◽  
Chest X Ray ◽  
Transformer Model

In the recent pandemic, accurate and rapid testing of patients remained a critical task in the diagnosis and control of COVID-19 disease spread in the healthcare industry. Because of the sudden increase in cases, most countries have faced scarcity and a low rate of testing. Chest X-rays have been shown in the literature to be a potential source of testing for COVID-19 patients, but manually checking X-ray reports is time-consuming and error-prone. Considering these limitations and the advancements in data science, we proposed a Vision Transformer-based deep learning pipeline for COVID-19 detection from chest X-ray-based imaging. Due to the lack of large data sets, we collected data from three open-source data sets of chest X-ray images and aggregated them to form a 30 K image data set, which is the largest publicly available collection of chest X-ray images in this domain to our knowledge. Our proposed transformer model effectively differentiates COVID-19 from normal chest X-rays with an accuracy of 98% along with an AUC score of 99% in the binary classification task. It distinguishes COVID-19, normal, and pneumonia patient’s X-rays with an accuracy of 92% and AUC score of 98% in the Multi-class classification task. For evaluation on our data set, we fine-tuned some of the widely used models in literature, namely, EfficientNetB0, InceptionV3, Resnet50, MobileNetV3, Xception, and DenseNet-121, as baselines. Our proposed transformer model outperformed them in terms of all metrics. In addition, a Grad-CAM based visualization is created which makes our approach interpretable by radiologists and can be used to monitor the progression of the disease in the affected lungs, assisting healthcare.

scholarly journals SPIDERS: overview of the X-ray galaxy cluster follow-up and the final spectroscopic data release

2020 ◽  
Vol 497 (3) ◽  
pp. 3976-3992 ◽  
Author(s):  
N Clerc ◽  
C C Kirkpatrick ◽  
A Finoguenov ◽  
R Capasso ◽  
J Comparat ◽  
...  
Keyword(s):  
Galaxy Clusters ◽  
Sample Selection ◽  
Galaxy Cluster ◽  
Sloan Digital Sky Survey ◽  
Observable Universe ◽  
Data Set ◽  
X Ray ◽  
Data Release ◽  
The Galaxy

ABSTRACT SPIDERS (The SPectroscopic IDentification of eROSITA Sources) is a large spectroscopic programme for X-ray selected galaxy clusters as part of the Sloan Digital Sky Survey-IV (SDSS-IV). We describe the final data set in the context of SDSS Data Release 16 (DR16): the survey overall characteristics, final targeting strategies, achieved completeness, and spectral quality, with special emphasis on its use as a galaxy cluster sample for cosmology applications. SPIDERS now consists of about 27 000 new optical spectra of galaxies selected within 4000 photometric red sequences, each associated with an X-ray source. The excellent spectrograph efficiency and a robust analysis pipeline yield a spectroscopic redshift measurement success rate exceeding 98 per cent, with a median velocity accuracy of 20 km s−1 (at z = 0.2). Using the catalogue of 2740 X-ray galaxy clusters confirmed with DR16 spectroscopy, we reveal the 3D map of the galaxy cluster distribution in the observable Universe up to z ∼ 0.6. We highlight the homogeneity of the member galaxy spectra among distinct regions of the galaxy cluster phase space. Aided by accurate spectroscopic redshifts and by a model of the sample selection effects, we compute the galaxy cluster X-ray luminosity function and we present its lack of evolution up to z = 0.6. Finally we discuss the prospects of forthcoming large multiplexed spectroscopic programmes dedicated to follow up the next generation of all-sky X-ray source catalogues.

scholarly journals Multiwavelength classification of X-ray selected galaxy cluster candidates using convolutional neural networks

2020 ◽  
Vol 496 (4) ◽  
pp. 4141-4153
Author(s):  
Matej Kosiba ◽  
Maggie Lieu ◽  
Bruno Altieri ◽  
Nicolas Clerc ◽  
Lorenzo Faccioli ◽  
...  
Keyword(s):  
Neural Networks ◽  
Galaxy Clusters ◽  
Convolutional Neural Networks ◽  
Galaxy Cluster ◽  
Optical Data ◽  
Data Set ◽  
Extended Source ◽  
X Ray ◽  
Extended Sources

ABSTRACT Galaxy clusters appear as extended sources in XMM–Newton images, but not all extended sources are clusters. So, their proper classification requires visual inspection with optical images, which is a slow process with biases that are almost impossible to model. We tackle this problem with a novel approach, using convolutional neural networks (CNNs), a state-of-the-art image classification tool, for automatic classification of galaxy cluster candidates. We train the networks on combined XMM–Newton X-ray observations with their optical counterparts from the all-sky Digitized Sky Survey. Our data set originates from the XMM CLuster Archive Super Survey (X-CLASS) survey sample of galaxy cluster candidates, selected by a specially developed pipeline, the XAmin, tailored for extended source detection and characterization. Our data set contains 1707 galaxy cluster candidates classified by experts. Additionally, we create an official Zooniverse citizen science project, The Hunt for Galaxy Clusters, to probe whether citizen volunteers could help in a challenging task of galaxy cluster visual confirmation. The project contained 1600 galaxy cluster candidates in total of which 404 overlap with the expert’s sample. The networks were trained on expert and Zooniverse data separately. The CNN test sample contains 85 spectroscopically confirmed clusters and 85 non-clusters that appear in both data sets. Our custom network achieved the best performance in the binary classification of clusters and non-clusters, acquiring accuracy of 90 per cent, averaged after 10 runs. The results of using CNNs on combined X-ray and optical data for galaxy cluster candidate classification are encouraging, and there is a lot of potential for future usage and improvements.

scholarly journals Anisotropy of the galaxy cluster X-ray luminosity–temperature relation

2018 ◽  
Vol 611 ◽  
pp. A50 ◽  
Author(s):  
Konstantinos Migkas ◽  
Thomas H. Reiprich
Keyword(s):  
Galaxy Clusters ◽  
Statistical Significance ◽  
Cosmological Parameters ◽  
Galaxy Cluster ◽  
Luminosity Distance ◽  
Temperature Relation ◽  
X Ray ◽  
Two Samples ◽  
The Galaxy ◽  
Group A

We introduce a new test to study the cosmological principle with galaxy clusters. Galaxy clusters exhibit a tight correlation between the luminosity and temperature of the X-ray-emitting intracluster medium. While the luminosity measurement depends on cosmological parameters through the luminosity distance, the temperature determination is cosmology-independent. We exploit this property to test the isotropy of the luminosity distance over the full extragalactic sky, through the normalization a of the LX–T scaling relation and the cosmological parameters Ωm and H0. To this end, we use two almost independent galaxy cluster samples: the ASCA Cluster Catalog (ACC) and the XMM Cluster Survey (XCS-DR1). Interestingly enough, these two samples appear to have the same pattern for a with respect to the Galactic longitude. More specifically, we identify one sky region within l ~ (−15°, 90°) (Group A) that shares very different best-fit values for the normalization of the LX–T relation for both ACC and XCS-DR1 samples. We use the Bootstrap and Jackknife methods to assess the statistical significance of these results. We find the deviation of Group A, compared to the rest of the sky in terms of a, to be ~2.7σ for ACC and ~3.1σ for XCS-DR1. This tension is not significantly relieved after excluding possible outliers and is not attributed to different redshift (z), temperature (T), or distributions of observable uncertainties. Moreover, a redshift conversion to the cosmic microwave background (CMB) frame does not have an important impact on our results. Using also the HIFLUGCS sample, we show that a possible excess of cool-core clusters in this region, is not able to explain the obtained deviations. Furthermore, we tested for a dependence of the results on supercluster environment, where the fraction of disturbed clusters might be enhanced, possibly affecting the LX–T relation. We indeed find a trend in the XCS-DR1 sample for supercluster members to be underluminous compared to field clusters. However, the fraction of supercluster members is similar in the different sky regions, so this cannot explain the observed differences, either. Constraining Ωm and H0 via the redshift evolution of LX–T and the luminosity distance via the flux–luminosity conversion, we obtain approximately the same deviation amplitudes as for a. It is interesting that the general observed behavior of Ωm for the sky regions that coincide with the CMB dipole is similar to what was found with other cosmological probes such as supernovae Ia. The reason for this behavior remains to be identified.

A batch-wise non-linear fitting and analysis tool for treating large X-ray diffraction data sets

2006 ◽  
Vol 39 (2) ◽  
pp. 262-266 ◽  
Author(s):  
R. J. Davies
Keyword(s):  
Diffraction Data ◽  
Operation Mode ◽  
Large Data ◽  
Scattering Data ◽  
Data Sets ◽  
Analysis Tool ◽  
Data Set ◽  
X Ray ◽  
Linear Fitting ◽  
Non Linear

Synchrotron sources offer high-brilliance X-ray beams which are ideal for spatially and time-resolved studies. Large amounts of wide- and small-angle X-ray scattering data can now be generated rapidly, for example, during routine scanning experiments. Consequently, the analysis of the large data sets produced has become a complex and pressing issue. Even relatively simple analyses become difficult when a single data set can contain many thousands of individual diffraction patterns. This article reports on a new software application for the automated analysis of scattering intensity profiles. It is capable of batch-processing thousands of individual data files without user intervention. Diffraction data can be fitted using a combination of background functions and non-linear peak functions. To compliment the batch-wise operation mode, the software includes several specialist algorithms to ensure that the results obtained are reliable. These include peak-tracking, artefact removal, function elimination and spread-estimate fitting. Furthermore, as well as non-linear fitting, the software can calculate integrated intensities and selected orientation parameters.

scholarly journals Lower resolution Laue neutron data yield correct nanocluster formulations

2014 ◽  
Vol 70 (a1) ◽  
pp. C187-C187
Author(s):  
Alison Edwards
Keyword(s):  
Neutron Diffraction ◽  
Single Crystal ◽  
Diffraction Pattern ◽  
Precise Determination ◽  
Data Sets ◽  
X Rays ◽  
Low Resolution ◽  
Neutron Data ◽  
X Ray ◽  
Product Formulation

"The renaissance in Laue studies - at neutron sources - provides us with access to single crystal neutron diffraction data for synthetic compounds without requiring synthesis of prohibitively large amounts of compound or improbably large crystals. Such neutron diffraction studies provide vital data where proof of the presence or absence of hydrogen in particular locations is required and which cannot validly be proved by X-ray studies. Since the commissioning of KOALA at OPAL in 2009[1] we have obtained numerous data sets which demonstrate the vital importance of measuring data even where the extent of the diffraction pattern is at relatively low resolution - especially when compared to that obtainable for the same compound with X-rays. In the Laue experiment performed with a fixed radius detector, data reduction is only feasible for crystals in the ""goldilocks"" zone – where the unit cell is relatively large for the detector, a correspondingly low resolution diffraction pattern in which adjacent spots are less affected by overlap will yield more data against which a structure can be refined than a pattern of higher resolution – one where neighbouring spots overlap rendering both unusable (in our current methodology). Analogous application of powder neutron diffraction in such determinations is also considered. Single crystal neutron diffraction studies of several important compounds (up to 5KDa see figure below)[2] in which precise determination of hydride content by neutron diffraction was pivotal to the final formulation will be presented. The neutron data sets typically possess 20% or fewer unique data at substantially "lower resolution" than the corresponding X-ray data sets. Careful refinement clearly reveals chemical detail which is typically unexplored in related X-ray diffraction studies reporting high profile chemistry despite the synthetic route being one which hydride ought to be considered/excluded in product formulation."

Structural study of the X-ray-induced enzymatic reaction of octahaem cytochromecnitrite reductase

2015 ◽  
Vol 71 (5) ◽  
pp. 1087-1094 ◽  
Author(s):  
A. A. Trofimov ◽  
K. M. Polyakov ◽  
V. A. Lazarenko ◽  
A. N. Popov ◽  
T. V. Tikhonova ◽  
...  
Keyword(s):  
Nitrite Reductase ◽  
Catalytic Reaction ◽  
Active Sites ◽  
Enzymatic Reaction ◽  
Absorbed Dose ◽  
Free Form ◽  
Data Sets ◽  
X Rays ◽  
X Ray ◽  
Site Water

Octahaem cytochromecnitrite reductase from the bacteriumThioalkalivibrio nitratireducenscatalyzes the reduction of nitrite to ammonium and of sulfite to sulfide. The reducing properties of X-ray radiation and the high quality of the enzyme crystals allow study of the catalytic reaction of cytochromecnitrite reductase directly in a crystal of the enzyme, with the reaction being induced by X-rays. Series of diffraction data sets with increasing absorbed dose were collected from crystals of the free form of the enzyme and its complexes with nitrite and sulfite. The corresponding structures revealed gradual changes associated with the reduction of the catalytic haems by X-rays. In the case of the nitrite complex the conversion of the nitrite ions bound in the active sites to NO species was observed, which is the beginning of the catalytic reaction. For the free form, an increase in the distance between the oxygen ligand bound to the catalytic haem and the iron ion of the haem took place. In the case of the sulfite complex no enzymatic reaction was detected, but there were changes in the arrangement of the active-site water molecules that were presumably associated with a change in the protonation state of the sulfite ions.

scholarly journals Finding COVID-19 from Chest X-rays using Deep Learning on a Small Dataset

2020 ◽  
Author(s):  
Lawrence Hall ◽  
Dmitry Goldgof ◽  
Rahul Paul ◽  
Gregory M. Goldgof
Keyword(s):  
False Negative ◽  
True Positive Rate ◽  
Small Data ◽  
Good Resolution ◽  
X Rays ◽  
True Positive ◽  
Data Set ◽  
X Ray ◽  
Negative Rate ◽  
Positive Rate

<p>Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative rate is projected to be as high as 30% and test results can take some time to obtain. X-ray machines are widely available and provide images for diagnosis quickly. This paper explores how useful chest X-ray images can be in diagnosing COVID-19 disease. We have obtained 135 chest X-rays of COVID-19 and 320 chest X-rays of viral and bacterial pneumonia. </p><p> A pre-trained deep convolutional neural network, Resnet50 was tuned on 102 COVID-19 cases and 102 other pneumonia cases in a 10-fold cross validation. The results were </p><p> an overall accuracy of 89.2% with a COVID-19 true positive rate of 0.8039 and an AUC of 0.95. Pre-trained Resnet50 and VGG16 plus our own small CNN were tuned or trained on a balanced set of COVID-19 and pneumonia chest X-rays. An ensemble of the three types of CNN classifiers was applied to a test set of 33 unseen COVID-19 and 218 pneumonia cases. The overall accuracy was 91.24% with the true positive rate for COVID-19 of 0.7879 with 6.88% false positives for a true negative rate of 0.9312 and AUC of 0.94. </p><p> This preliminary study has flaws, most critically a lack of information about where in the disease process the COVID-19 cases were and the small data set size. More COVID-19 case images at good resolution will enable a better answer to the question of how useful chest X-rays can be for diagnosing COVID-19.</p>

159 The Need Of Six Monthly Follow Up X-Rays Post Total Knee Replacement(TKR)

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
N Baig ◽  
M Ferrari ◽  
A Lukaszewicz
Keyword(s):  
Total Knee Replacement ◽  
Knee Replacement ◽  
Trauma Centre ◽  
X Rays ◽  
Data Set ◽  
X Ray ◽  
Major Trauma Centre ◽  
Plain Films ◽  
Total Knee

Abstract Background There is a longstanding culture of repeat x-rays after total knee replacement (TKR) as part of follow up, often combined with a clinic review. This is to check that the prosthesis is in a satisfactory position. There are inherently a number of issues with this historic approach including exposure of patients to further radiation who may be asymptomatic, time delays in busy clinics or x-ray departments and costs. Objectives The aim of this audit was to assess whether follow up plain films after TKR are methodically undertaken and of benefit to confirm satisfactory appearance if immediate post -operative x-rays were unremarkable. The findings of a six month follow up x-ray was specifically evaluated. The secondary aim was to establish the timing of further follow up x-rays within the department. Method 200 patients were included within the analysis, they all received a TKR at a major trauma centre, over a one-year period between December 2017 and December 2018. Results It was found that 100% of those patients having a post-operative film had a satisfactory appearance. 78% of patients had at least one further follow op x-ray of which 99.4% were satisfactory. Up to five follow up x-rays were taken with 53.5% of patients having a follow up x-ray at 6 months. Conclusions From the above results there is minimal, if any, evidence within the data set to support routine, additional follow up imaging if initial post-operative films are satisfactory, and the patient is asymptomatic.

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