Imaging of the Paranasal Sinuses: Plain-Film Radiography, Computed Tomography, and Magnetic Resonance Imaging

Mafee, Mahmood F.; Farid, Nikdokht; Lim, Wei Yen

doi:10.1007/978-1-4939-0265-1_17

Cited by 2 publications

(2 citation statements)

References 35 publications

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“…With the help of an LED applicator, the maxillary sinuses were probed and the subsequent registration of diaphanograms was carried out using a CMOS camera UI-3240CP-NIR-GL Rev.2 with a Pentax C1614-M (KP) lens (Pentax, Japan) located opposite the patient's face. A literary analysis of the spectral properties of maxillary sinuses and human head tissues in norm and pathology, as well as an analysis of previous studies on employment of the diaphanoscopy technique, showed that the use of 650 and 850 nm probing wavelengths is promising owing to relatively small absorption [14,28,29]. In addition, pathologies with an exudate component are better visualized at a wavelength of 850 nm, while for pathologies involving plethora a wavelength of 650 nm is preferable.…”

Section: Experimental System and Methodologymentioning

confidence: 99%

Digital diaphanoscopy of maxillary sinus pathologies supported by machine learning

Bryanskaya

Dremin

Shupletsov

et al. 2023

Journal of Biophotonics

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Maxillary sinus pathologies remain among the most common ENT diseases requiring timely diagnosis for successful treatment. Standard ENT inspection approaches indicate low sensitivity in detecting maxillary sinus pathologies. In this paper, we report on capabilities of digital diaphanoscopy combined with machine learning tools in the detection of such pathologies. We provide a comparative analysis of two machine learning approaches applied to digital diapahnoscopy data, namely, convolutional neural networks and linear discriminant analysis. The sensitivity and specificity values obtained for both employed approaches exceed the reported accuracy indicators for traditional screening diagnosis methods (such as nasal endoscopy or ultrasound), suggesting the prospects of their usage for screening maxillary sinuses alterations. The analysis of the obtained values showed that the linear discriminant analysis, being a simpler approach as compared to neural networks, allows one to detect the maxillary sinus pathologies with the sensitivity and specificity of 0.88 and 0.98, respectively.

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Section: Experimental System and Methodologymentioning

confidence: 99%

Digital diaphanoscopy of maxillary sinus pathologies supported by machine learning

Bryanskaya

Dremin

Shupletsov

et al. 2023

Journal of Biophotonics

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“…It allows assessing the general condition of the paranasal sinuses and makes it possible to detect the presence of liquid content (along with formed cysts or polyps) in them, as well as the changes in the mucous membrane. If there is a pathological change in sinus pneumatization, then the resulting image will show significant darkening along the upper horizontal level, asymmetry of the inflamed sinuses, narrowing of the nasal passages, and mucosal thickening [ 4 ]. Despite the advantages of this technique, its application in clinical practice is limited to assessments that help to identify the degree of development of a pathological process which already has pronounced signs to determine further treatment tactics and the need for surgical interventions.…”

Section: Introductionmentioning

confidence: 99%

Optical Diagnostics of the Maxillary Sinuses by Digital Diaphanoscopy Technology

et al. 2021

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The work is devoted to the development of a scientific and technical basis for instrument implementation of a digital diaphanoscopy technology for the diagnosis of maxillary sinus inflammatory diseases taking into account the anatomical features of patients (differences in skin structure, skull bone thickness, and sinus size), the optical properties of exercised tissues, and the age and gender characteristics of patients. The technology is based on visualization and analysis of scattering patterns of low-intensity radiation as it passes through the maxillary sinuses. The article presents the experimental data obtained using the digital diaphanoscopy method and the results of numerical simulation of the optical radiation passage through the study area. The experimental setup has been modernized through the installation of a a device for controlling the LED applicator brightness. The approach proposed may have considerable promise for creating diagnostic criteria for various pathological changes and can be used to assess the differences in the optical and anatomical features of males and females.

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Imaging of the Paranasal Sinuses: Plain-Film Radiography, Computed Tomography, and Magnetic Resonance Imaging

Cited by 2 publications

References 35 publications

Digital diaphanoscopy of maxillary sinus pathologies supported by machine learning

Digital diaphanoscopy of maxillary sinus pathologies supported by machine learning

Optical Diagnostics of the Maxillary Sinuses by Digital Diaphanoscopy Technology

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