scholarly journals Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 338 ◽  
Author(s):  
Franko Hržić ◽  
Ivan Štajduhar ◽  
Sebastian Tschauner ◽  
Erich Sorantin ◽  
Jonatan Lerga
Keyword(s):  
Image Segmentation ◽  
False Negative ◽  
Local Entropy ◽  
Fracture Detection ◽  
Initial Image ◽  
Data Set ◽  
X Ray ◽  
Accuracy And Precision ◽  
The Difference ◽  
Analysis System

The paper proposes a segmentation and classification technique for fracture detection in X-ray images. This novel rotation-invariant method introduces the concept of local entropy for de-noising and removing tissue from the analysed X-ray images, followed by an improved procedure for image segmentation and the detection of regions of interest. The proposed local Shannon entropy was calculated for each image pixel using a sliding 2D window. An initial image segmentation was performed on the entropy representation of the original image. Next, a graph theory-based technique was implemented for the purpose of removing false bone contours and improving the edge detection of long bones. Finally, the paper introduces a classification and localisation procedure for fracture detection by tracking the difference between the extracted contour and the estimation of an ideal healthy one. The proposed hybrid method excels at detecting small fractures (which are hard to detect visually by a radiologist) in the ulna and radius bones—common injuries in children. Therefore, it is imperative that a radiologist inspecting the X-ray image receives a warning from the computerised X-ray analysis system, in order to prevent false-negative diagnoses. The proposed method was applied to a data-set containing 860 X-ray images of child radius and ulna bones (642 fracture-free images and 218 images containing fractures). The obtained results showed the efficiency and robustness of the proposed approach, in terms of segmentation quality and classification accuracy and precision (up to 91.16 % and 86.22 % , respectively).

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

scholarly journals Detection of Fracture Bones in X-ray Images Categorization

2020 ◽  
pp. 1-11
Author(s):  
Adigun Oyeranmi ◽  
Babatunde Ronke ◽  
Rufai Mohammed ◽  
Aigbokhan Edwin
Keyword(s):  
Feature Extraction ◽  
Performance Metrics ◽  
Confusion Matrix ◽  
False Negative ◽  
Support Vector ◽  
Kappa Statistics ◽  
Fracture Detection ◽  
True Negative ◽  
Research Attention ◽  
X Ray

Fractured bone detection and categorization is currently receiving research attention in computer aided diagnosis system because of the ease it has brought to doctors in classification and interpretation of X-ray images.  The choice of an efficient algorithm or combination of algorithms is paramount to accurately detect and categorize fractures in X-ray images, which is the first stage of diagnosis in treatment and correction of damaged bones for patients. This is what this research seeks to address. The research design involves data collection, preprocessing, segmentation, feature extraction, classification and evaluation of the proposed method. The sample dataset were x-ray images collected from the Department of Radiology, National Orthopedic Hospital, Igbobi-Lagos, Nigeria as well as Open Access Medical Image Repositories. The image preprocessing involves the conversion of images in RGB format to grayscale, sharpening and smoothing using Unsharp Masking Tool.  The segmentation of the preprocessed image was carried out by adopting the Entropy method in the first stage and Canny edge method in the second stage while feature extraction was performed using Hough Transformation. Detection and classification of fracture image employed a combination of two algorithms;  K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) for detecting fracture locations based on four classification types: (normal, comminute, oblique and transverse).Two performance assessment methods were employed to evaluate the developed system. The first evaluation was based on confusion matrix which evaluates fracture and non-fracture on the basis of TP (True Positive), TN (True negative), FP (False Positive) and FN (False Negative). The second appraisal was based on Kappa Statistics which evaluates the type of fracture by determining the accuracy of the categorized fracture bone type. The result of first assessment for fracture detection shows that 26 out of 40 preprocessed images were fractured, resulting to the following three values of performance metrics: accuracy value of 90%, sensitivity of 87% and specificity of 100%. The Kappa coefficient error assessment produced accuracy of 83% during classification. The proposed method can find suitable use in categorization of fracture types on different bone images based on the results obtained from the experiment.

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>

A Ccomparison of sedigraph and pipette methods for soil particle-size analysis

Soil Research ◽  
1993 ◽  
Vol 31 (4) ◽  
pp. 407 ◽  
Author(s):  
GD Buchan ◽  
KS Grewal ◽  
JJ Claydon ◽  
RJ Mcpherson
Keyword(s):  
Particle Size ◽  
New Zealand ◽  
Particle Size Analysis ◽  
Size Analysis ◽  
Data Sets ◽  
Regression Equations ◽  
Total Iron Content ◽  
Data Set ◽  
X Ray ◽  
The Difference

The X-ray attenuation (Sedigraph) method for particle-size analysis is known to consistently estimate a finer size distribution than the pipette method. The objectives of this study were to compare the two methods, and to explore the reasons for their divergence. The methods are compared using two data sets from measurements made independently in two New Zealand laboratories, on two different sets of New Zealand soils, covering a range of textures and parent materials. The Sedigraph method gave systematically greater mass percentages at the four measurement diameters (20, 10, 5 and 2 �m). For one data set, the difference between clay (<2 �m) percentages from the two methods is shown to be positively correlated (R2 = 0.625) with total iron content of the sample, for all but one of the soils. This supports a novel hypothesis that the typically greater concentration of Fe (a strong X-ray absorber) in smaller size fractions is the major factor causing the difference. Regression equations are presented for converting the Sedigraph data to their pipette equivalents.

Diagnostic image quality of hand-held and wall-mounted X-ray devices in bitewing radiography: a non-inferiority clinical trial

2021 ◽  
pp. 20200471
Author(s):  
Reinier Cornelis Hoogeveen ◽  
Siham Ouchene ◽  
WER Berkhout
Keyword(s):  
Clinical Trial ◽  
Image Quality ◽  
Future Research ◽  
Diagnostic Image Quality ◽  
Data Set ◽  
Diagnostic Image ◽  
X Ray ◽  
The Difference ◽  
Diagnostic Modalities

Objectives: The present clinical trial was intended to clarify whether subjective assessments of diagnostic X-ray image quality achieved via hand-held (HH) Nomad Pro 2 (KaVo Kerr, Brea, CA, USA) X-ray device is non-inferior that of the wall-mounted (WM) KaVo Focus (KaVo Dental, Bieberich, Germany). Methods: A prospective, cross-over, and in vivo non-inferiority clinical trial was conducted to compare these two diagnostic modalities. Based on sampling calculations, 205 patients were selected for study, generating 410 paired bitewing radiographs in randomized sequence. The films were assessed independently, engaging three observers blinded to modality for random, side-by-side-comparisons. Diagnostic image quality was rated as follows: no preference, HH preference, or WM preference. Observer judgements were combined accordingly to reach a majority. Results: Collective observer ratings indicated no preference for diagnostic image quality in 63.9% of cases, with WM preference at 16.6% and HH preference at 19.5%. The difference in HH and WM preferences (19.5%–16.6% = 2.9%) was within the expected 95% confidence interval. Majority agreement was reached in 82.7%. Conclusions: Subjectively assessed diagnostic image quality in bitewing radiographs acquired by HH and WM devices did not differ significantly. The hand-held device is thus non-inferior to the WM in this regard. Our data set of paired bitewing radiographs may subsequently aid in future research.

scholarly journals Archaeometallurgical Investigations of the Early Iron Age Casting Workshop at Kamieniec. A Preliminary Study

2016 ◽  
Vol 16 (3) ◽  
pp. 29-34 ◽  
Author(s):  
A. Garbacz-Klempka ◽  
Ł. Kowalski ◽  
J. Kozana ◽  
J. Gackowski ◽  
M. Perek-Nowak ◽  
...  
Keyword(s):  
Iron Age ◽  
Energy Dispersive ◽  
Data Set ◽  
X Ray ◽  
Xrf Scanning ◽  
Non Local ◽  
Preliminary Study ◽  
Dendritic Microstructures ◽  
Analysis System ◽  
Shrinkage Cavities

Abstract This preliminary study characterizes the bronze metalworking on a defensive settlement of the Lusatian culture in former Kamieniec (Chełmno land, Poland) as it is reflected through casting workshop recovered during recent excavations. Among ready products, the ones giving evidence of local metallurgy (e.g. casting moulds and main runners) were also identified. With the shrinkage cavities and dendritic microstructures revealed, the artifacts prove the implementing a casting method by the Lusatian culture metalworkers. The elemental composition indicates application of two main types of bronzes: Cu-Sn and Cu-Pb. Aside these main alloying additions, some natural impurities such as silver, arsenic, antimony and nickel were found which may be attributed to the origin of the ore and casting technology. The collection from Kamieniec was described in terms of its structure and composition. The investigations were made by means of the energy dispersive X-ray fluorescence spectroscopy (ED-XRF), scanning electron microscopy (SEM) coupled with an energy dispersive X-ray analysis system (EDS) and optical microscopy (OM). In order to fingerprint either local or non-local profile of the alloys, the ED-XRF data-set was statistically evaluated using a factor analysis (FA).

scholarly journals Supergiant fast X-ray transients versus classical supergiant high mass X-ray binaries: Does the difference lie in the companion wind?

2018 ◽  
Vol 610 ◽  
pp. A50 ◽  
Author(s):  
P. Pradhan ◽  
E. Bozzo ◽  
B. Paul
Keyword(s):  
Stellar Wind ◽  
Equivalent Width ◽  
High Mass ◽  
Stellar Winds ◽  
Data Set ◽  
Iron Line ◽  
X Ray ◽  
Eclipse Observations ◽  
The Difference ◽  
X Ray Binaries

We present a comparative study of stellar winds in classical supergiant high mass X-ray binaries (SgXBs) and supergiant fast X-ray transients (SFXTs) based on the analysis of publicly available out-of-eclipse observations performed with Suzaku and XMM-Newton. Our data set includes 55 observations of classical SgXBs and 21 observations of SFXTs. We found that classical SgXBs are characterized by a systematically higher absorption and luminosity compared to the SFXTs, confirming the results of previous works in the literature. Additionally, we show that the equivalent width of the fluorescence Kα iron line in the classical SgXBs is significantly larger than that of the SFXTs (outside X-ray eclipses). Based on our current understanding of the physics of accretion in these systems, we conclude that the most likely explanation of these differences is ascribed to the presence of mechanisms inhibiting accretion most of the time in SFXTs, thereby leading to a much less efficient photoionization of the stellar wind compared to classical SgXBs. We do not find evidence for the previously reported anticorrelation between the equivalent width of the fluorescence iron line and the luminosity of SgXBs.

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 ◽  
False Negative Rate ◽  
Disease Process ◽  
Small Data ◽  
X Rays ◽  
Data Set ◽  
X Ray ◽  
Set Size ◽  
Lack Of Information ◽  
Chest X Ray

<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 122 chest X-rays of COVID-19 and over 4,000 chest X-rays of viral and bacterial pneumonia. A pre-trained deep convolutional neural network has been tuned on 102 COVID-19 cases and 102 other pneumonia cases in a 10-fold cross validation. The results were all 102 COVID-19 cases were correctly classified and there were 8 false positives resulting in an AUC of 0.997. On a test set of 20 unseen COVID-19 cases all were correctly classified and more than 95% of 4,171 other pneumonia examples were correctly classified. This 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 will enable a better answer to the question of how useful chest X-rays can be for diagnosing COVID-19 (so please send them). </p>

Octuple cuvette for small-angle X-ray solution scattering

2011 ◽  
Vol 44 (6) ◽  
pp. 1294-1296 ◽  
Author(s):  
Shuji Akiyama ◽  
Takaaki Hikima
Keyword(s):  
Bovine Serum Albumin ◽  
Small Angle ◽  
Infinite Dilution ◽  
Average Deviation ◽  
Data Set ◽  
Scattering Intensity ◽  
X Ray ◽  
X Ray Scattering ◽  
Fast Acquisition ◽  
The Difference

A new octuple cuvette has been developed to reduce the experimental time in small-angle X-ray scattering (SAXS). Since each chamber has uniform dimensions, identical scattering curves for bovine serum albumin are obtained within an average deviation of 1%. The cuvette can be used to record SAXS curves for seven sample concentrations quasi-simultaneously by interchamber subtraction,i.e.calculating the difference in scattering intensity between the sample in any of the first seven chambers and a matching buffer in the eighth chamber. This enables fast acquisition of a data set and its extrapolation to infinite dilution, and increases the throughput of SAXS experiments.

Crystallization and preliminary X-ray analysis of the periplasmic receptor (PotF) of the putrescine transport system in Escherichia coli

1998 ◽  
Vol 54 (1) ◽  
pp. 132-134 ◽  
Author(s):  
Dmitry G. Vassylyev ◽  
Tatsuki Kashiwagi ◽  
Hideyuki Tomitori ◽  
Keiko Kashiwagi ◽  
Kazuei Igarashi ◽  
...  
Keyword(s):  
Transport System ◽  
Heavy Atom ◽  
Hanging Drop ◽  
Data Set ◽  
X Ray ◽  
E Coli ◽  
Diffusion Technique ◽  
Cell Dimensions ◽  
The Difference ◽  
Unit Cell Dimensions

The primary receptor (PotF) of the putrescine transport system in E. coli has been crystallized by the hanging-drop vapor-diffusion technique. The crystals belong to the space group P21212 with unit-cell dimensions a = 269.4, b = 82.33 and c = 93.74 Å. The crystals diffract beyond 2.2 Å with a rotating-anode X-ray source. A complete data set from the native crystals has been collected and processed at 2.3 Å resolution. Two heavy-atom derivatives have been prepared from the same Pt compound at 293 and 277 K. The difference Patterson maps revealed completely different major heavy-atom sites between these two derivatives.

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