Back to Search Start Over

Possibilities of Automated Diagnostics of Odontogenic Sinusitis According to the Computer Tomography Data

Authors :
Oleg G. Avrunin
Yana V. Nosova
Ibrahim Younouss Abdelhamid
Sergii V. Pavlov
Natalia O. Shushliapina
Waldemar Wójcik
Piotr Kisała
Aliya Kalizhanova
Source :
Sensors, Vol 21, Iss 4, p 1198 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Individual anatomical features of the paranasal sinuses and dentoalveolar system, the complexity of physiological and pathophysiological processes in this area, and the absence of actual standards of the norm and typical pathologies lead to the fact that differential diagnosis and assessment of the severity of the course of odontogenic sinusitis significantly depend on the measurement methods of significant indicators and have significant variability. Therefore, an urgent task is to expand the diagnostic capabilities of existing research methods, study the significance of the measured indicators, and substantiate the expediency of their use in the diagnosis of specific pathologies in an automated mode. Methods of digital filtering, image segmentation and analysis, fluid dynamics, and statistical and discriminant analysis were used. Preliminary differential diagnosis of odontogenic sinusitis can be performed by densitemetric analysis of tomographic images of the maxillary sinuses, performed using frontal multiplanar reconstructions according to a given algorithm. The very manifestation of the characteristic changes in the densitography of the maxillary sinus allows for the initiation of certain pathological processes and permits the development of the effectiveness of the diagnosis of the pathology of the sinus sinuses, which can be realized automatically in real life.

Details

Language :
English
ISSN :
14248220
Volume :
21
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.909b43b064e453498332fc25f00d753
Document Type :
article
Full Text :
https://doi.org/10.3390/s21041198