Possibilities of Automated Diagnostics of Odontogenic Sinusitis According to the Computer Tomography Data
Oleg G. Avrunin,
Yana V. Nosova,
Ibrahim Younouss Abdelhamid,
Sergii V. Pavlov,
Natalia O. Shushliapina,
Waldemar Wójcik,
Piotr Kisała,
Aliya Kalizhanova
Affiliations
Oleg G. Avrunin
Department of Biomedical Engineering, Faculty of Electronic and Biomedical Engineering Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
Yana V. Nosova
Department of Biomedical Engineering, Faculty of Electronic and Biomedical Engineering Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
Ibrahim Younouss Abdelhamid
Department of Biomedical Engineering, Faculty of Electronic and Biomedical Engineering Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
Sergii V. Pavlov
Department of Biomedical Engineering, Vinnytsia National Technical University, 21021 Vinnytsia, Ukraine
Natalia O. Shushliapina
Department of Otorhinolaryngology, Stomatological Faculty Kharkiv National Medical University, 61022 Kharkiv, Ukraine
Waldemar Wójcik
Institute of Electronic and Information Technologies, Faculty Electrical Engineering and Computer Science, Lublin University of Technology, 20-618 Lublin, Poland
Piotr Kisała
Institute of Electronic and Information Technologies, Faculty Electrical Engineering and Computer Science, Lublin University of Technology, 20-618 Lublin, Poland
Aliya Kalizhanova
Institute of Information and Computational Technologies CS MES RK, 050010 Almaty, Kazakhstan
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.
