ANALYSIS OF UPPER RESPIRATORY TRACT SEGMENTATION FEATURES TO DETERMINE NASAL CONDUCTANCE

Oleg Avrunin

oleh.avrunin@nure.ua
Kharkiv National University of Radio Electronics (Ukraine)
http://orcid.org/0000-0002-6312-687X

Yana Nosova


Kharkiv National University of Radio Electronics (Ukraine)
http://orcid.org/0000-0003-4310-5833

Nataliia Shushliapina


Kharkiv National Medical University (Ukraine)
http://orcid.org/0000-0002-6347-3150

Ibrahim Younouss Abdelhamid


Kharkiv National University of Radio Electronics (Ukraine)
http://orcid.org/0000-0003-2611-2417

Oleksandr Avrunin


Kharkiv National University of Radio Electronics (Ukraine)
http://orcid.org/0000-0002-5202-0770

Svetlana Kyrylashchuk


Vinnytsia National Technical University (Ukraine)
http://orcid.org/0000-0002-8972-3541

Olha Moskovchuk


Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University (Ukraine)
http://orcid.org/0000-0003-4568-1607

Orken Mamyrbayev


Institute of Information and Computational Technologies of the Kazakh National Technical University named after K. I. Satbayev (Kazakhstan)
http://orcid.org/0000-0001-8318-3794

Abstract

The paper examines the features of segmentation of the upper respiratory tract to determine nasal air conduction. 2D and 3D illustrations of the segmentation process and the obtained results are given. When forming an analytical model of the aerodynamics of the nasal cavity, the main indicator that characterizes the configuration of the nasal canal is the equivalent diameter, which is determined at each intersection of the nasal cavity. It is calculated based on the area and perimeter of the corresponding section of the nasal canal. When segmenting the nasal cavity, it is first necessary to eliminate air structures that do not affect the aerodynamics of the upper respiratory tract - these are, first of all, intact spaces of the paranasal sinuses, in which diffuse air exchange prevails. In the automatic mode, this is possible by performing the elimination of unconnected isolated areas and finding the difference coefficients of the areas connected by confluences with the nasal canal in the next step. High coefficients of difference of sections between intersections will indicate the presence of separated areas and contribute to their elimination. The complex configuration and high individual variability of the structures of the nasal cavity does not allow segmentation to be fully automated, but this approach contributes to the absence of interactive correction in 80% of tomographic datasets. The proposed method, which takes into account the intensity of the image elements close to the contour ones, allows to reduce the averaging error from tomographic reconstruction up to 2 times due to artificial sub-resolution. The perspective of the work is the development of methods for fully automatic segmentation of the structures of the nasal cavity, taking into account the individual anatomical variability of the upper respiratory tract.


Keywords:

aerodynamics of nasal breathing, nasal cavity, tomographic reconstruction, segmentation, upper respiratory tract, air conduction

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Published
2022-12-30

Cited by

Avrunin, O., Nosova, Y., Shushliapina, N., Abdelhamid, I. Y., Avrunin, O., Kyrylashchuk, S., … Mamyrbayev, O. (2022). ANALYSIS OF UPPER RESPIRATORY TRACT SEGMENTATION FEATURES TO DETERMINE NASAL CONDUCTANCE. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(4), 35–40. https://doi.org/10.35784/iapgos.3274

Authors

Oleg Avrunin 
oleh.avrunin@nure.ua
Kharkiv National University of Radio Electronics Ukraine
http://orcid.org/0000-0002-6312-687X

Authors

Yana Nosova 

Kharkiv National University of Radio Electronics Ukraine
http://orcid.org/0000-0003-4310-5833

Authors

Nataliia Shushliapina 

Kharkiv National Medical University Ukraine
http://orcid.org/0000-0002-6347-3150

Authors

Ibrahim Younouss Abdelhamid 

Kharkiv National University of Radio Electronics Ukraine
http://orcid.org/0000-0003-2611-2417

Authors

Oleksandr Avrunin 

Kharkiv National University of Radio Electronics Ukraine
http://orcid.org/0000-0002-5202-0770

Authors

Svetlana Kyrylashchuk 

Vinnytsia National Technical University Ukraine
http://orcid.org/0000-0002-8972-3541

Authors

Olha Moskovchuk 

Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University Ukraine
http://orcid.org/0000-0003-4568-1607

Authors

Orken Mamyrbayev 

Institute of Information and Computational Technologies of the Kazakh National Technical University named after K. I. Satbayev Kazakhstan
http://orcid.org/0000-0001-8318-3794

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