scholarly journals Detection of the bone contours of the knee joints on medical X-ray images

2019 ◽  
Vol 43 (3) ◽  
pp. 455-463
Author(s):  
А.A. Mikhaylichenko ◽  
Y.М. Demyanenko

Detection of objects of interest is a crucial step in the automatic analysis of the medical X-ray images. However, medical X-rays are often characterized by the low contrast as well as great variability in range of colours, which makes it more difficult to be analysed by the common methods based on the regions homogeneity principles. In our paper, we present an alternative approach to the contours detection problem that does not require the homogeneity criteria to be satisfied. Our method is based on the identification of edge fragments and elimination of discontinuities between them. Moreover, we describe a numeric criterion for quality evaluation of contours detection. The obtained results can used for diagnosis of abnormalities and diseases, and also as an intermediate step for more sophisticated methods of image analysis.

2018 ◽  
Vol 14 (S346) ◽  
pp. 83-87
Author(s):  
Vikram V. Dwarkadas

AbstractMassive stars lose a considerable amount of mass during their lifetime. When the star explodes as a supernova (SN), the resulting shock wave expands in the medium created by the stellar mass-loss. Thermal X-ray emission from the SN depends on the square of the density of the ambient medium, which in turn depends on the mass-loss rate (and velocity) of the progenitor wind. The emission can therefore be used to probe the stellar mass-loss in the decades or centuries before the star’s death.We have aggregated together data available in the literature, or analysed by us, to compute the X-ray lightcurves of almost all young supernovae detectable in X-rays. We use this database to explore the mass-loss rates of massive stars that collapse to form supernovae. Mass-loss rates are lowest for the common Type IIP supernovae, but increase by several orders of magnitude for the highest luminosity X-ray SNe.


1996 ◽  
Vol 06 (03n04) ◽  
pp. 523-530 ◽  
Author(s):  
M. YONEZAWA ◽  
Y. MATSUDA ◽  
F. NISHIYAMA

It is important for maintenance and understanding of health to make inquiries into the biological defence mechanisms. Yonezawa et al. came across an induction of yet unknown defence mechanisms in mice which acquired two types of radioresistance (decrease in bone-marrow death rate after midlethal exposure): one occured 2 weeks after preirradiation with 0.3–0.5 Gy and the other 2 months after 0.05–0.10 Gy of X-rays. To elucidate the acquired radioresistance induced after preirradiation with 0.5 Gy (in a shorter time case). recovery of blood cell counts after sublethal irradiation were measured in mice of ICR strain. Contrary to the common knowledge on radiation protection. recovery of blood cell counts of thrombocytes. leukocytes and erythrocytes after sublethal irradiation were not stimulated by the preirradiation. This study was planned to find some keys to elucidate the mechanism for the acquired radioresistance. Eleven elements. Cl. K. Ca. Cr. Mn. Fe. Ni. Cu. Zn. Se and Br. were analysed clearly in mice sera by PIXE.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Feng Li ◽  
Fatih Porikli

This paper presents a computationally very efficient, robust, automatic tracking method that does not require any implanted fiducials for low-contrast tumors. First, it generates a set of motion hypotheses and computes corresponding feature vectors in local windows within orthogonal-axis X-ray images. Then, it fits a regression model that maps features to 3D tumor motions by minimizing geodesic distances on motion manifold. These hypotheses can be jointly generated in 3D to learn a single 3D regression model or in 2D through back projection to learn two 2D models separately. Tumor is tracked by applying regression to the consecutive image pairs while selecting optimal window size at every time. Evaluations are performed on orthogonal X-ray videos of 10 patients. Comparative experimental results demonstrate superior accuracy (~1 pixel average error) and robustness to varying imaging artifacts and noise at the same time.


2019 ◽  
Vol 34 (2) ◽  
pp. 103-109
Author(s):  
Arnold C. Vermeulen ◽  
Christopher M. Kube ◽  
Nicholas Norberg

In this paper, we will report about the implementation of the self-consistent Kröner–Eshelby model for the calculation of X-ray elastic constants for general, triclinic crystal symmetry. With applying appropriate symmetry relations, the point groups of higher crystal symmetries are covered as well. This simplifies the implementation effort to cover the calculations for any crystal symmetry. In the literature, several models can be found to estimate the polycrystalline elastic properties from single crystal elastic constants. In general, this is an intermediate step toward the calculation of the polycrystalline response to different techniques using X-rays, neutrons, or ultrasonic waves. In the case of X-ray residual stress analysis, the final goal is the calculation of X-ray Elastic constants. Contrary to the models of Reuss, Voigt, and Hill, the Kröner–Eshelby model has the benefit that, because of the implementation of the Eshelby inclusion model, it can be expanded to cover more complicated systems that exhibit multiple phases, inclusions or pores and that these can be optionally combined with a polycrystalline matrix that is anisotropic, i.e., contains texture. We will discuss a recent theoretical development where the approaches of calculating bounds of Reuss and Voigt, the tighter bounds of Hashin–Shtrikman and Dederichs–Zeller are brought together in one unifying model that converges to the self-consistent solution of Kröner–Eshelby. For the implementation of the Kröner–Eshelby model the well-known Voigt notation is adopted. The 4-rank tensor operations have been rewritten into 2-rank matrix operations. The practical difficulties of the Voigt notation, as usually concealed in the scientific literature, will be discussed. Last, we will show a practical X-ray example in which the various models are applied and compared.


2019 ◽  
Vol 26 (6) ◽  
pp. 1996-2012 ◽  
Author(s):  
K. Medjanik ◽  
S. V. Babenkov ◽  
S. Chernov ◽  
D. Vasilyev ◽  
B. Schönhense ◽  
...  

An alternative approach to hard-X-ray photoelectron spectroscopy (HAXPES) has been established. The instrumental key feature is an increase of the dimensionality of the recording scheme from 2D to 3D. A high-energy momentum microscope detects electrons with initial kinetic energies up to 8 keV with a k-resolution of 0.025 Å−1, equivalent to an angular resolution of 0.034°. A special objective lens with k-space acceptance up to 25 Å−1 allows for simultaneous full-field imaging of many Brillouin zones. Combined with time-of-flight (ToF) parallel energy recording this yields maximum parallelization. Thanks to the high brilliance (1013 hν s−1 in a spot of <20 µm diameter) of beamline P22 at PETRA III (Hamburg, Germany), the microscope set a benchmark in HAXPES recording speed, i.e. several million counts per second for core-level signals and one million for d-bands of transition metals. The concept of tomographic k-space mapping established using soft X-rays works equally well in the hard X-ray range. Sharp valence band k-patterns of Re, collected at an excitation energy of 6 keV, correspond to direct transitions to the 28th repeated Brillouin zone. Measured total energy resolutions (photon bandwidth plus ToF-resolution) are 62 meV and 180 meV FWHM at 5.977 keV for monochromator crystals Si(333) and Si(311) and 450 meV at 4.0 keV for Si(111). Hard X-ray photoelectron diffraction (hXPD) patterns with rich fine structure are recorded within minutes. The short photoelectron wavelength (10% of the interatomic distance) `amplifies' phase differences, making full-field hXPD a sensitive structural tool.


2017 ◽  
Vol 9 (5) ◽  
pp. 631-636 ◽  
Author(s):  
Mohamed Faisal Chevidikunnan ◽  
Amer Al Saif ◽  
Harish Pai K ◽  
Lawrence Mathias

AbstractBackgroundThe Q angle is a relevant clinical diagnostic measurement to detect various disorders of the knee. The common method used to measure the Q angle in the routine clinical practice is by radiography. An alternative to radiographic measurement is goniometry, by which exposure to x-rays can be avoided.ObjectivesTo compare and correlate the goniometric measurement of Q angle with radiographic measurement of the Q angle in patients with acute knee pain.MethodsWe selected 45 patient participants with a mean age of 32.5 years who satisfied the inclusion criteria for this study. All the patients underwent goniometric measurement of the Q angle followed by x-ray imaging of the entire lower limb. Later the bony prominences were marked on the x-ray image and the Q angle formed was measured using a protractor. The Pearson correlation coefficient between the goniometric and radiographic measurements was determined.ResultsWe found a significant relationship between Q angles obtained using a goniometer and x-ray imaging in the supine position (r = 0.91, P = 0.001). The mean difference between the goniometric measurement of Q angle and the radiographic measurement was 0.1°, which is not significant.ConclusionsGoniometry can be used to measure Q angle as accurately as radiography, and can be used as an inexpensive and radiation free alternative.


2020 ◽  
Vol 39 (3) ◽  
pp. 2893-2907 ◽  
Author(s):  
Huaiguang Wu ◽  
Pengjie Xie ◽  
Huiyi Zhang ◽  
Daiyi Li ◽  
Ming Cheng

The chest X-ray examination is one of the most important methods for screening and diagnosing of many lung diseases. Diagnosis of pneumonia by chest X-ray is one of the common methods used by medical experts. However, the image quality of chest X-Ray has some defects, such as low contrast, overlapping organs and blurred boundary, which seriously affects detecting pneumonia in chest X-rays. Therefore, it has important medical value and application significance to construct a stable and accurate automatic detection model of pneumonia through a large number of chest X-ray images. In this paper, we propose a novel hybrid system for detecting pneumonia from chest X-Ray image: ACNN-RF, which is an adaptive median filter Convolutional Neural Network (CNN) recognition model based on Random forest (RF). Firstly, the improved adaptive median filtering is employed to remove noise in the chest X-ray image, which makes the image more easily recognized. Secondly, we establish the CNN architecture based on Dropout to extract deep activation features from each chest X-ray image. Finally, we employ the RF classifier based on GridSearchCV class as a classifier for deep activation features in CNN model. It not only avoids the phenomenon of over-fitting in data training, but also improves the accuracy of image classification. During our experiment, the public chest X-ray image dataset used in the experiment contains 5863 images, which comprises 4265 frontal-view X-ray images of 1574 unique patients. The average recognition rate of pneumonia is up to 97% by the proposed ACNN-RF. The experimental results show that the ACNN-RF identification system is more effective than the previous traditional image identification system.


1997 ◽  
Vol 04 (02) ◽  
pp. 343-352 ◽  
Author(s):  
MAURIZIO SACCHI

A short overview is given of recent developments in the use of polarized X-rays. A few studies are chosen to exemplify the possible applications and the common underlying ideas of different spectroscopic techniques in the domain of soft X-rays. The analysis of resonant reflectivity of polarized X-rays from a magnetic sample is discussed in more detail.


2021 ◽  
Vol 37 (5A) ◽  
pp. 166-171
Author(s):  
Israa S. Abed

The lungs are portion of a complex unit, enlarging and relaxing numerus times every day to supply oxygen and exude CO2. Lung disease might occur from troubles in any part of it. Carcinoma often called Cancer is the generally rising and it is the most harmful disease happened in humankind. Carcinoma occurs because of uncontrolled growth of malignant cells inside the tissues of the lungs. Earlier diagnosis of cancer can help save large numbers of lives, while any delay or fail in detection may cause additional serious problems leading to sudden fatal death. The objective of this study is to design an automated system with an ability to improve the detection process in order to perform advanced recognition of the disease. The diagnosis techniques include: X-rays, MRI, CT images etc. X-ray is the common and low-cost technique that is widely used and it is relatively available for everyone. Rather than new techniques like CT and MRI, X-ray is human dependable, meaning it needs a Doctor and X-ray specialist in order to determine lung cases, so developing a system which can enhance and aid in diagnosis, can help specialist to determine cases in easily.


2021 ◽  
Vol 37 ◽  
pp. 00043
Author(s):  
Elena Lyubchenko ◽  
Irina Bondarenko ◽  
Tatyana Timofeeva

To diagnose hip dysplasia, you can use a test system, the essence of which is to create a subhabitation in the hip joint of the dog, laid on the side, while there is a click in the joint, which means that the test is positive, while the pressure on the knee joint of the hip joint does not happen. The most common method of diagnosing dysplasia worldwide is X-ray, in which the age of the dogs studied should be more than a year, and large and giant breeds are studied in the range of one to one and a half years, with the animal laid on the back so that the X-ray image shows the pelvis with the wings of the iliac bone and femurs, including the knee joints, therefore, it is also necessary to use sedation, which allows you to comply with all the requirements for styling. The resulting X-rays are assessed according to the main Xray characteristics of the hip joint, taking measurements on six parameters presented in the text of this article, and determining the type of dysplasia. Computed tomography and magnetic resonance imaging can reveal the instability of the pathology in the hip joint and improve understanding of the disease process.


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