Aspects of X-ray diagnostics of inflammatory processes in the maxillary sinuses

2021 ◽  
pp. 4-10
Author(s):  
A.P. Arzhantsev
Keyword(s):  
Computed Tomography ◽  
Multislice Computed Tomography ◽  
Maxillary Sinusitis ◽  
The State ◽  
X Ray ◽  
The Face ◽  
Inflammatory Processes ◽  
X Ray Computed ◽  
Diagnostic Capabilities ◽  
Maxillary Sinuses

Studying the characteristics X-ray pictures of the maxillary sinuses more than 350 patients with odontogenic diseases of the maxillary sinuses and no odontogenic of origin, as well as images of the maxillary sinuses in normal. We used data of orthopantomography, panoramic zonography middle and upper areas of the face, radiography of the paranasal sinuses, cone-beam and multislice computed tomography. Diseases of the maxillary sinuses characterized by a variety of origin and X-ray manifestations, which makes the complexity of the diagnosis. In this regard, the necessary knowledge of X-ray skialogicheskih features of pathological processes and the efficiency of X-ray techniques to objective detect not only the changes in the sinuses, but the factors causing the them. Multi -projection X-ray computed tomography examination of the maxillary sinus and alveolar process of the maxilla is a reliable method of assessing the state of the maxillary sinuses and the differentiation of the origin of maxillary sinusitis. Common dental X-ray techniques are limited diagnostic capabilities of assessing the state of the mucous membrane and the walls of the maxillary sinuses, which must be considered when interpreting the image.

scholarly journals The Use of Computed Tomography for the Study of Chronic Maxillary Sinusitis: Based on Crania from the Pucará De Tilcara Fortress, Argentina

2020 ◽  
Vol 48 (3) ◽  
pp. 143-153
Author(s):  
A. V. Zubova ◽  
N. I. Ananyeva ◽  
V. G. Moiseyev ◽  
I. K. Stulov ◽  
L. M. Dmitrenko ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Maxillary Sinusitis ◽  
Secondary Infection ◽  
Ostiomeatal Complex ◽  
Odontogenic Origin ◽  
X Ray Computed ◽  
Chronic Maxillary Sinusitis ◽  
Relationship Of ◽  
Skeletal Samples ◽  
Maxillary Sinuses

We discuss the methodological advantages of using X-ray computed tomography (CT) for diagnosing chronic maxillary sinusitis (CMS) of various etiologies on skeletal samples. A CT examination of 20 crania from the Pucará de Tilcara fortress, Argentina (late 8th to 16th centuries AD), was carried out. Criteria for identifying CMS included osteitic lesions in the form of focal destruction, and thickened and sclerotized walls of maxillary sinuses. To determine the etiology of the disease, a tomographic and macroscopic examination of the dentition and bones of the ostiomeatal complex were performed, the presence or absence of facial injuries was assessed, and the co-occurrence of various pathologies was statistically evaluated. Five cases of CMS were identified. Four of these may be of odontogenic origin; in two cases, a secondary infection of the maxillary sinuses is possible. In one instance, the etiology was not determined. No indications of traumatic infection were found. Statistical analysis revealed a relationship of CMS with apical periodontitis and the ante-mortem loss of upper molars and premolars. An indirect symptom of CMS may be the remodeled bone tissue and porosity of the posterior surface of the maxilla.

X-Ray Computed Tomography of Ultralightweight Metals

1999 ◽  
Vol 11 (1) ◽  
pp. 199-211
Author(s):  
J. M. Winter ◽  
R. E. Green ◽  
A. M. Waters ◽  
W. H. Green
Keyword(s):  
Computed Tomography ◽  
X Ray ◽  
X Ray Computed

scholarly journals Nano- scale X-ray Computed Tomography: Morphological Analysis of Fuel Cell Electrodes

2013 ◽  
Vol 19 (S2) ◽  
pp. 630-631
Author(s):  
P. Mandal ◽  
W.K. Epting ◽  
S. Litster
Keyword(s):  
Computed Tomography ◽  
Fuel Cell ◽  
Morphological Analysis ◽  
Fuel Cell Electrodes ◽  
X Ray ◽  
Nano Scale ◽  
X Ray Computed

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

scholarly journals Ant Colony-Based Hyperparameter Optimisation in Total Variation Reconstruction in X-ray Computed Tomography

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 591
Author(s):  
Manasavee Lohvithee ◽  
Wenjuan Sun ◽  
Stephane Chretien ◽  
Manuchehr Soleimani
Keyword(s):  
Computed Tomography ◽  
Total Variation ◽  
Cross Validation ◽  
Ant Colony ◽  
Reference Image ◽  
X Ray ◽  
X Ray Computed ◽  
Hyperparameter Selection ◽  
The Cross ◽  
Optimal Set

In this paper, a computer-aided training method for hyperparameter selection of limited data X-ray computed tomography (XCT) reconstruction was proposed. The proposed method employed the ant colony optimisation (ACO) approach to assist in hyperparameter selection for the adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm, which is a total-variation (TV) based regularisation algorithm. During the implementation, there was a colony of artificial ants that swarm through the AwPCSD algorithm. Each ant chose a set of hyperparameters required for its iterative CT reconstruction and the correlation coefficient (CC) score was given for reconstructed images compared to the reference image. A colony of ants in one generation left a pheromone through its chosen path representing a choice of hyperparameters. Higher score means stronger pheromones/probabilities to attract more ants in the next generations. At the end of the implementation, the hyperparameter configuration with the highest score was chosen as an optimal set of hyperparameters. In the experimental results section, the reconstruction using hyperparameters from the proposed method was compared with results from three other cases: the conjugate gradient least square (CGLS), the AwPCSD algorithm using the set of arbitrary hyperparameters and the cross-validation method.The experiments showed that the results from the proposed method were superior to those of the CGLS algorithm and the AwPCSD algorithm using the set of arbitrary hyperparameters. Although the results of the ACO algorithm were slightly inferior to those of the cross-validation method as measured by the quantitative metrics, the ACO algorithm was over 10 times faster than cross—Validation. The optimal set of hyperparameters from the proposed method was also robust against an increase of noise in the data and can be applicable to different imaging samples with similar context. The ACO approach in the proposed method was able to identify optimal values of hyperparameters for a dataset and, as a result, produced a good quality reconstructed image from limited number of projection data. The proposed method in this work successfully solves a problem of hyperparameters selection, which is a major challenge in an implementation of TV based reconstruction algorithms.

scholarly journals Three‐dimensional X‐ray‐computed tomography of 3300‐ to 6000‐year‐old Citrullus seeds from Libya and Egypt compared to extant seeds throws doubts on species assignments

2021 ◽  
Author(s):  
Katherine A. Wolcott ◽  
Guillaume Chomicki ◽  
Yannick M. Staedler ◽  
Krystyna Wasylikowa ◽  
Mark Nesbitt ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
X Ray ◽  
X Ray Computed
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