scholarly journals Enhanced Wavelets Transform Edge Detection Technique for X-Ray Images.

2020 ◽  
Vol 9 (6) ◽  
pp. 596-599
Keyword(s):  
Edge Detection ◽  
Wavelet Transforms ◽  
Bone Fractures ◽  
Imaging Techniques ◽  
Research Area ◽  
Discrete Wavelet ◽  
X Rays ◽  
X Ray ◽  
Image Objects ◽  
Aided Diagnosis

Target edge detection is one of the crucial and indispensable process used to detect the size of the fracture by using multi resolution discrete wavelet transforms in image processing field. It is a foremost step of image enhancement and is prior to segmentation procedure.Computerised imaging techniques such as X-ray, CT, Ultrasound and MRI are used by the radiologist helps in diagnosing diseases. Digital x-rays are economically agile helps in detecting microscopic bone fracture which are not detectable by human eye. The paper involve the use of daubechies wavelet transform (db1) undergoes multi resolution three level wavelet decomposition that isolate into higher and lower frequencies readily, results in finding edges in horizontal and vertical function which is the necessary aspect of edge detection for x ray images.Matlab code have been implemented for testing the boundaries of the image objects in authentic digital x ray images as well as for the standard dataset images. Computer-aided diagnosis system (CADD) is becoming a popular research area in diagnosing x-ray bone fractures,bone cancerdiseases

Studies of metaphase chromosomes in the scanning transmission x-ray microscope: Image fidelity, radiation damage and specimen preparation

1992 ◽  
Vol 50 (2) ◽  
pp. 1038-1039
Author(s):  
Shawn Williams ◽  
Xiaodong Zhang ◽  
Susan Lamm ◽  
Jack Van’t Hof
Keyword(s):  
Visible Light ◽  
Radiation Damage ◽  
Cross Section ◽  
Imaging Techniques ◽  
Dose Range ◽  
Specimen Preparation ◽  
X Rays ◽  
Metaphase Chromosomes ◽  
X Ray ◽  
Scanning Transmission

The Scanning Transmission X-ray Microscope (STXM) is well suited for investigating metaphase chromosome structure. The absorption cross-section of soft x-rays having energies between the carbon and oxygen K edges (284 - 531 eV) is 6 - 9.5 times greater for organic specimens than for water, which permits one to examine unstained, wet biological specimens with resolution superior to that attainable using visible light. The attenuation length of the x-rays is suitable for imaging micron thick specimens without sectioning. This large difference in cross-section yields good specimen contrast, so that fewer soft x-rays than electrons are required to image wet biological specimens at a given resolution. But most imaging techniques delivering better resolution than visible light produce radiation damage. Soft x-rays are known to be very effective in damaging biological specimens. The STXM is constructed to minimize specimen dose, but it is important to measure the actual damage induced as a function of dose in order to determine the dose range within which radiation damage does not compromise image quality.

An x-ray microprobe based upon a close-coupled focal-spot / glass capillary arrangement

1992 ◽  
Vol 50 (2) ◽  
pp. 1758-1759
Author(s):  
D. A. Carpenter ◽  
M. A. Taylor
Keyword(s):  
Imaging Techniques ◽  
Fluorescence Analysis ◽  
High Sensitivity ◽  
Specimen Preparation ◽  
X Rays ◽  
Glass Capillary ◽  
Close Coupling ◽  
X Ray ◽  
Point To Point ◽  
Beam Damage

The development of intense sources of x rays has led to renewed interest in the use of microbeams of x rays in x-ray fluorescence analysis. Sparks pointed out that the use of x rays as a probe offered the advantages of high sensitivity, low detection limits, low beam damage, and large penetration depths with minimal specimen preparation or perturbation. In addition, the option of air operation provided special advantages for examination of hydrated systems or for nondestructive microanalysis of large specimens.The disadvantages of synchrotron sources prompted the development of laboratory-based instrumentation with various schemes to maximize the beam flux while maintaining small point-to-point resolution. Nichols and Ryon developed a microprobe using a rotating anode source and a modified microdiffractometer. Cross and Wherry showed that by close-coupling the x-ray source, specimen, and detector, good intensities could be obtained for beam sizes between 30 and 100μm. More importantly, both groups combined specimen scanning with modern imaging techniques for rapid element mapping.

scholarly journals Optimization of X-ray Investigations in Dentistry Using Optical Coherence Tomography

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4554
Author(s):  
Ralph-Alexandru Erdelyi ◽  
Virgil-Florin Duma ◽  
Cosmin Sinescu ◽  
George Mihai Dobre ◽  
Adrian Bradu ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Radiation Dose ◽  
Imaging Techniques ◽  
Image Resolution ◽  
Optical Coherence ◽  
X Rays ◽  
High Quality ◽  
X Ray

The most common imaging technique for dental diagnoses and treatment monitoring is X-ray imaging, which evolved from the first intraoral radiographs to high-quality three-dimensional (3D) Cone Beam Computed Tomography (CBCT). Other imaging techniques have shown potential, such as Optical Coherence Tomography (OCT). We have recently reported on the boundaries of these two types of techniques, regarding. the dental fields where each one is more appropriate or where they should be both used. The aim of the present study is to explore the unique capabilities of the OCT technique to optimize X-ray units imaging (i.e., in terms of image resolution, radiation dose, or contrast). Two types of commercially available and widely used X-ray units are considered. To adjust their parameters, a protocol is developed to employ OCT images of dental conditions that are documented on high (i.e., less than 10 μm) resolution OCT images (both B-scans/cross sections and 3D reconstructions) but are hardly identified on the 200 to 75 μm resolution panoramic or CBCT radiographs. The optimized calibration of the X-ray unit includes choosing appropriate values for the anode voltage and current intensity of the X-ray tube, as well as the patient’s positioning, in order to reach the highest possible X-rays resolution at a radiation dose that is safe for the patient. The optimization protocol is developed in vitro on OCT images of extracted teeth and is further applied in vivo for each type of dental investigation. Optimized radiographic results are compared with un-optimized previously performed radiographs. Also, we show that OCT can permit a rigorous comparison between two (types of) X-ray units. In conclusion, high-quality dental images are possible using low radiation doses if an optimized protocol, developed using OCT, is applied for each type of dental investigation. Also, there are situations when the X-ray technology has drawbacks for dental diagnosis or treatment assessment. In such situations, OCT proves capable to provide qualitative images.

scholarly journals Truncated Inception Net: COVID-19 Outbreak Screening using Chest X-rays

2020 ◽  
Author(s):  
Dipayan Das ◽  
KC Santosh ◽  
Umapada Pal
Keyword(s):  
Neural Network ◽  
World Wide ◽  
Imaging Techniques ◽  
Imaging Systems ◽  
Ct Scans ◽  
X Rays ◽  
X Ray ◽  
X Ray Imaging ◽  
Proposed Model ◽  
Different Types

Abstract Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in less than a couple of months, and the infection, caused by SARS-CoV-2, is spreading at an unprecedented rate. AI-driven tools are used to identify Coronavirus outbreaks as well as forecast their nature of spread, where imaging techniques are widely used, such as CT scans and chest X-rays (CXRs). In this paper, motivated by the fact that X-ray imaging systems are more prevalent and cheaper than CT scan systems, a deep learning-based Convolutional Neural Network (CNN) model, which we call Truncated Inception Net, is proposed to screen COVID-19 positive CXRs from other non-COVID and/or healthy cases. To validate our proposal, six different types of datasets were employed by taking the following CXRs: COVID-19 positive, Pneumonia positive, Tuberculosis positive, and healthy cases into account. The proposed model achieved an accuracy of 99.96% (AUC of 1.0) in classifying COVID- 19 positive cases from combined Pneumonia and healthy cases. Similarly, it achieved an accuracy of 99.92% (AUC of 0.99) in classifying COVID-19 positive cases from combined Pneumonia, Tuberculosis and healthy CXRs. To the best of our knowledge, as of now, the achieved results outperform the existing AI-driven tools for screening COVID-19 using CXRs.

scholarly journals Optimization of the energy for Breast monochromatic absorption X-ray Computed Tomography

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Pasquale Delogu ◽  
Vittorio Di Trapani ◽  
Luca Brombal ◽  
Giovanni Mettivier ◽  
Angelo Taibi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Imaging Techniques ◽  
Fixed Dose ◽  
X Rays ◽  
Reconstruction Algorithms ◽  
Contrast Resolution ◽  
X Ray ◽  
X Ray Imaging ◽  
X Ray Computed ◽  
Dose Levels

Abstract The limits of mammography have led to an increasing interest on possible alternatives such as the breast Computed Tomography (bCT). The common goal of all X-ray imaging techniques is to achieve the optimal contrast resolution, measured through the Contrast to Noise Ratio (CNR), while minimizing the radiological risks, quantified by the dose. Both dose and CNR depend on the energy and the intensity of the X-rays employed for the specific imaging technique. Some attempts to determine an optimal energy for bCT have suggested the range 22 keV–34 keV, some others instead suggested the range 50 keV–60 keV depending on the parameters considered in the study. Recent experimental works, based on the use of monochromatic radiation and breast specimens, show that energies around 32 keV give better image quality respect to setups based on higher energies. In this paper we report a systematic study aiming at defining the range of energies that maximizes the CNR at fixed dose in bCT. The study evaluates several compositions and diameters of the breast and includes various reconstruction algorithms as well as different dose levels. The results show that a good compromise between CNR and dose is obtained using energies around 28 keV.

scholarly journals K-edge Subtraction Computed Tomography with a Compact Synchrotron X-ray Source

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Stephanie Kulpe ◽  
Martin Dierolf ◽  
Benedikt Günther ◽  
Madleen Busse ◽  
Klaus Achterhold ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Contrast Agent ◽  
Imaging Techniques ◽  
X Rays ◽  
Synchrotron Source ◽  
X Ray ◽  
Inverse Compton Scattering ◽  
Inverse Compton ◽  
X Ray Computed ◽  
Compact Light Source

Abstract In clinical diagnosis, X-ray computed tomography (CT) is one of the most important imaging techniques. Yet, this method lacks the ability to differentiate similarly absorbing substances like commonly used iodine contrast agent and calcium which is typically seen in calcifications, kidney stones and bones. K-edge subtraction (KES) imaging can help distinguish these materials by subtracting two CT scans recorded at different X-ray energies. So far, this method mostly relies on monochromatic X-rays produced at large synchrotron facilities. Here, we present the first proof-of-principle experiment of a filter-based KES CT method performed at a compact synchrotron X-ray source based on inverse-Compton scattering, the Munich Compact Light Source (MuCLS). It is shown that iodine contrast agent and calcium can be clearly separated to provide CT volumes only showing one of the two materials. These results demonstrate that KES CT at a compact synchrotron source can become an important tool in pre-clinical research.

scholarly journals COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images

2020 ◽  
Vol 10 (16) ◽  
pp. 5683 ◽  
Author(s):  
Lourdes Duran-Lopez ◽  
Juan Pedro Dominguez-Morales ◽  
Jesús Corral-Jaime ◽  
Saturnino Vicente-Diaz ◽  
Alejandro Linares-Barranco
Keyword(s):  
Deep Learning ◽  
Imaging Techniques ◽  
Learning System ◽  
Screening Process ◽  
X Ray ◽  
Average Accuracy ◽  
Rapid Spread ◽  
Chest X Ray ◽  
And Control ◽  
Aided Diagnosis

The COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 has changed the world as we know it. An early diagnosis is crucial in order to prevent new outbreaks and control its rapid spread. Medical imaging techniques, such as X-ray or chest computed tomography, are commonly used for this purpose due to their reliability for COVID-19 diagnosis. Computer-aided diagnosis systems could play an essential role in aiding radiologists in the screening process. In this work, a novel Deep Learning-based system, called COVID-XNet, is presented for COVID-19 diagnosis in chest X-ray images. The proposed system performs a set of preprocessing algorithms to the input images for variability reduction and contrast enhancement, which are then fed to a custom Convolutional Neural Network in order to extract relevant features and perform the classification between COVID-19 and normal cases. The system is trained and validated using a 5-fold cross-validation scheme, achieving an average accuracy of 94.43% and an AUC of 0.988. The output of the system can be visualized using Class Activation Maps, highlighting the main findings for COVID-19 in X-ray images. These promising results indicate that COVID-XNet could be used as a tool to aid radiologists and contribute to the fight against COVID-19.

scholarly journals A Content Based Approach to Medical X-Ray Image Retrieval using Texture Features

2014 ◽  
Vol 12 (7) ◽  
pp. 3742-3748 ◽  
Author(s):  
Sumathi Ganesan ◽  
T.S. Subashini
Keyword(s):  
Image Retrieval ◽  
Imaging Techniques ◽  
Texture Features ◽  
X Rays ◽  
Query Image ◽  
City Block ◽  
X Ray ◽  
Important Research Topic ◽  
Similar Images ◽  
The City

Of late, the amount of digital X-ray images that are produced in hospitals is increasing incredibly fast. Efficient storing, processing and retrieving of X-ray images have thus become an important research topic. With the exponential need that arises in the search for the clinically relevant and visually similar medical images over a vast database, the arena of digital imaging techniques is forced to provide a potential and path-breaking methodology in the midst of technical advancements so as to give the best match in accordance to the user’s query image. CBIR helps doctors to compare X-rays of their current patients with images from similar cases and they could also use these images as queries to find the similar entries in the X-ray database. This paper focuses on six different classes of X-ray images, viz. chest, skull, foot, spine, pelvic and palm for efficient image retrieval. Initially the various X-rays are automatically classified into the six-different classes using BPNN and SVM as classifiers and GLCM co-efficient as features for classification. Indexing is done to make the retrieval fast and retrieval of similar images is based on the city block distance.  

scholarly journals Hard X-ray omnidirectional differential phase and dark-field imaging

2021 ◽  
Vol 118 (9) ◽  
pp. e2022319118
Author(s):  
Hongchang Wang ◽  
Kawal Sawhney
Keyword(s):  
Imaging Techniques ◽  
Dark Field ◽  
X Rays ◽  
Contrast Imaging ◽  
X Ray ◽  
Differential Phase ◽  
Dark Field Imaging ◽  
Spiral Path ◽  
Wide Range ◽  
Phase Images

Ever since the discovery of X-rays, tremendous efforts have been made to develop new imaging techniques for unlocking the hidden secrets of our world and enriching our understanding of it. X-ray differential phase contrast imaging, which measures the gradient of a sample’s phase shift, can reveal more detail in a weakly absorbing sample than conventional absorption contrast. However, normally only the gradient’s component in two mutually orthogonal directions is measurable. In this article, omnidirectional differential phase images, which record the gradient of phase shifts in all directions of the imaging plane, are efficiently generated by scanning an easily obtainable, randomly structured modulator along a spiral path. The retrieved amplitude and main orientation images for differential phase yield more information than the existing imaging methods. Importantly, the omnidirectional dark-field images can be simultaneously extracted to study strongly ordered scattering structures. The proposed method can open up new possibilities for studying a wide range of complicated samples composed of both heavy, strongly scattering atoms and light, weakly scattering atoms.

scholarly journals News on the X-ray emission from hot subdwarf stars

2017 ◽  
Vol 26 (1) ◽  
Author(s):  
Nicola La Palombara ◽  
Sandro Mereghetti
Keyword(s):  
Neutron Star ◽  
Binary Systems ◽  
High Sensitivity ◽  
Research Area ◽  
X Rays ◽  
Low Mass Stars ◽  
X Ray ◽  
Low Mass ◽  
Hot Subdwarfs ◽  
Weak Winds

AbstractIn latest years, the high sensitivity of the instruments on-board the XMM-Newton and Chandra satellites allowed us to explore the properties of the X-ray emission from hot subdwarf stars. The small but growing sample of X-ray detected hot subdwarfs includes binary systems, in which the X-ray emission is due to wind accretion onto a compact companion (white dwarf or neutron star), as well as isolated sdO stars, in which X-rays are probably due to shock instabilities in the wind. X-ray observations of these low-mass stars provide information which can be useful for our understanding of the weak winds of this type of stars and can lead to the discovery of particularly interesting binary systems. Here we report the most recent results we have recently obtained in this research area.

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