SU-C-209-06: Improving X-Ray Imaging with Computer Vision and Augmented Reality

2016 ◽  
Vol 43 (6Part3) ◽  
pp. 3329-3329 ◽  
Author(s):  
R.D. MacDougall ◽  
S Don ◽  
B Scherrer
Keyword(s):  
Computer Vision ◽  
Augmented Reality ◽  
X Ray ◽  
X Ray Imaging

scholarly journals Advanced Object Detection in Bio-Medical X-Ray Images for Anomaly Detection and Recognition

2021 ◽  
Vol 12 (2) ◽  
pp. 93-110
Author(s):  
Garv Modwel ◽  
Anu Mehra ◽  
Nitin Rakesh ◽  
K. K. Mishra
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Vision System ◽  
Human Vision ◽  
Biomedical Image Processing ◽  
X Ray ◽  
Biomedical Image ◽  
X Ray Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Result Analysis

The human vision system is mimicked in the format of videos and images in the area of computer vision. As humans can process their memories, likewise video and images can be processed and perceptive with the help of computer vision technology. There is a broad range of fields that have great speculation and concepts building in the area of application of computer vision, which includes automobile, biomedical, space research, etc. The case study in this manuscript enlightens one about the innovation and future scope possibilities that can start a new era in the biomedical image-processing sector. A pre-surgical investigation can be perused with the help of the proposed technology that will enable the doctors to analyses the situations with deeper insight. There are different types of biomedical imaging such as magnetic resonance imaging (MRI), computerized tomographic (CT) scan, x-ray imaging. The focused arena of the proposed research is x-ray imaging in this subset. As it is always error-prone to do an eyeball check for a human when it comes to the detailing. The same applied to doctors. Subsequently, they need different equipment for related technologies. The methodology proposed in this manuscript analyses the details that may be missed by an expert doctor. The input to the algorithm is the image in the format of x-ray imaging; eventually, the output of the process is a label on the corresponding objects in the test image. The tool used in the process also mimics the human brain neuron system. The proposed method uses a convolutional neural network to decide on the labels on the objects for which it interprets the image. After some pre-processing the x-ray images, the neural network receives the input to achieve an efficient performance. The result analysis is done that gives a considerable performance in terms of confusion factor that is represented in terms of percentage. At the end of the narration of the manuscript, future possibilities are being traces out to the limelight to conduct further research.

Defects of Platelet Function Recognized by X-Ray Imaging and Scanning Electron Microscopy

1985 ◽  
Vol 43 ◽  
pp. 610-613
Author(s):  
M.G. Baldini ◽  
S. Morinaga ◽  
D. Minasian ◽  
R. Feder ◽  
D. Sayre ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Cell Biology ◽  
Imaging Technique ◽  
Human Platelets ◽  
X Rays ◽  
X Ray ◽  
X Ray Imaging ◽  
Complex Phenomena ◽  
Scanning Electron

Contact X-ray imaging is presently developing as an important imaging technique in cell biology. Our recent studies on human platelets have demonstrated that the cytoskeleton of these cells contains photondense structures which can preferentially be imaged by soft X-ray imaging. Our present research has dealt with platelet activation, i.e., the complex phenomena which precede platelet appregation and are associated with profound changes in platelet cytoskeleton. Human platelets suspended in plasma were used. Whole cell mounts were fixed and dehydrated, then exposed to a stationary source of soft X-rays as previously described. Developed replicas and respective grids were studied by scanning electron microscopy (SEM).

Designing high-resolution slow scan CCD-based TEM camera systems

1992 ◽  
Vol 50 (2) ◽  
pp. 946-947
Author(s):  
James F. Mancuso ◽  
William B. Maxwell ◽  
Russell E. Camp ◽  
Mark H. Ellisman
Keyword(s):  
Fiber Optics ◽  
Ccd Camera ◽  
High Energy ◽  
Phosphor Layer ◽  
X Ray ◽  
Light Production ◽  
Camera Systems ◽  
X Ray Imaging ◽  
Electron Image ◽  
Scintillating Fiber

The imaging requirements for 1000 line CCD camera systems include resolution, sensitivity, and field of view. In electronic camera systems these characteristics are determined primarily by the performance of the electro-optic interface. This component converts the electron image into a light image which is ultimately received by a camera sensor.Light production in the interface occurs when high energy electrons strike a phosphor or scintillator. Resolution is limited by electron scattering and absorption. For a constant resolution, more energy deposition occurs in denser phosphors (Figure 1). In this respect, high density x-ray phosphors such as Gd2O2S are better than ZnS based cathode ray tube phosphors. Scintillating fiber optics can be used instead of a discrete phosphor layer. The resolution of scintillating fiber optics that are used in x-ray imaging exceed 20 1p/mm and can be made very large. An example of a digital TEM image using a scintillating fiber optic plate is shown in Figure 2.

Ionic homeostasis and subcellular element compartmentation

1990 ◽  
Vol 48 (2) ◽  
pp. 150-151
Author(s):  
Ann LeFurgey ◽  
Peter Ingram ◽  
J.J. Blum ◽  
M.C. Carney ◽  
L.A. Hawkey ◽  
...  
Keyword(s):  
Leishmania Major ◽  
Ionic Homeostasis ◽  
X Ray ◽  
Functional Studies ◽  
Cell Compartments ◽  
X Ray Imaging ◽  
Resolution Electron ◽  
Multiple Cell ◽  
Role Of Zn

Subcellular compartments commonly identified and analyzed by high resolution electron probe x-ray microanalysis (EPXMA) include mitochondria, cytoplasm and endoplasmic or sarcoplasmic reticulum. These organelles and cell regions are of primary importance in regulation of cell ionic homeostasis. Correlative structural-functional studies, based on the static probe method of EPXMA combined with biochemical and electrophysiological techniques, have focused on the role of these organelles, for example, in maintaining cell calcium homeostasis or in control of excitation-contraction coupling. New methods of real time quantitative x-ray imaging permit simultaneous examination of multiple cell compartments, especially those areas for which both membrane transport properties and element content are less well defined, e.g. nuclei including euchromatin and heterochromatin, lysosomes, mucous granules, storage vacuoles, microvilli. Investigations currently in progress have examined the role of Zn-containing polyphosphate vacuoles in the metabolism of Leishmania major, the distribution of Na, K, S and other elements during anoxia in kidney cell nuclel and lysosomes; the content and distribution of S and Ca in mucous granules of cystic fibrosis (CF) nasal epithelia; the uptake of cationic probes by mltochondria in cultured heart ceils; and the junctional sarcoplasmic retlculum (JSR) in frog skeletal muscle.

Dynamic X-ray imaging of the penetration of boron carbide

2000 ◽  
Vol 10 (PR9) ◽  
pp. Pr9-583-Pr9-588 ◽  
Author(s):  
W. A. Gooch ◽  
M. S. Burkins ◽  
G. Hauver ◽  
P. Netherwood ◽  
R. Benck
Keyword(s):  
Boron Carbide ◽  
X Ray ◽  
X Ray Imaging

X-Ray Imaging

2020 ◽  
Author(s):  
Keyword(s):  
X Ray ◽  
X Ray Imaging

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

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