Аnalysis of groups of textural features to identify the symptom of ground-glass opacity in computed tomography images of the lungs
- 1,3 Image Processing Systems Institute, NRC «Kurchatov Institute»; Samara National Research University
- 2 Image Processing Systems Institute, NRC «Kurchatov Institute»
Abstract
Today, medical specialists have to work with various pulmonary diseases and their symptoms. One of these symptoms is the ground glass opacity, diagnosed in various diseases. The purpose of this work is to develop a technology for detecting the ground glass opacity symptom on computed tomography images of the lungs based on the analysis of groups of texture features. This technology is based on calculating the information space of groups of texture features of the lungs, segmented in the source image. In the process of developing the technology, the most informative group was identified, which made it possible to achieve an accuracy of classification of the ground glass opacity symptom of 94,7%.
- Received
- 12.12.2023
- Approved after review
- 15.01.2024
- Accepted
- 05.02.2024
How to cite
Ильясова Н.Ю., Лякин М.Я., Демин Н.С. Выявление симптома матового стекла на изображениях компьютерной томографии лёгких на основе анализа групп текстурных признаков // Биомедицинская радиоэлектроника. 2024. T. 27. № 2. С. 13−17. DOI: https://doi.org/10.18127/j15604136-202402-02
References
- Zavershinskij A.V. Simptom «matovogo stekla». Byulleten' medicinskih internet-konferencij. 2016. T. 6. № 6. S. 1201.
- Hodosh E.M., Efremova O.A., Horoshun D.A. Simptom «matovogo stekla»: kliniko-luchevaya parallel'. Nauchnye vedomosti Belgorodskogo gosudarstvennogo universiteta. Seriya: Medicina. Farmaciya. 2014. № 18(189). S. 11–23.
- Shchekina S.A., Balykova L.A., Selezneva N.M. Granulematoz s poliangiitom. Klinicheskaya medicina. 2020. T. 98. № 5. S. 378–382.
- Safanova T.D., Shejh Zh.V. KT-priznak «matovoe steklo» pri granulematoze s poliangiitom i vnebol'nichnoj pnevmonii. Medicinskaya vizualizaciya. 2023. T. 27. № 2. S. 62–70.
- Bestaev D.V., Bozh'eva L.A. Kliniko-laboratornye i instrumental'nye osobennosti bol'nyh revmatoidnym artritom s komp'yuterno-tomograficheskim simptomom intersticial'nogo porazheniya legkih «matovoe steklo». Vestnik novyh medicinskih tekhnologij. 2015. № 1. S. 19–24.
- Kovalyov I.L. Teksturnye priznaki izobrazhenij: metod. ukazaniya. Minsk: BNTU. 2010. 26 s.
- Yakovleva E.V., Nesterova E.P. Sravnitel'nyj analiz metodov harakteristik Lavsa i matric sovpadenij v zadachah segmentacii teksturnyh izobrazhenij. Prikladnaya radioelektronika. 2009. T. 8. № 2. C. 181–187.
- Strzelecki M., Szczypinski P., Materka A., Klepaczko A. A software tool for automatic classification and segmentation of 2D/3D medical images. Nuclear Instruments and Methods In Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2013. V. 702. P. 137–140.
- Il'yasova N.Yu., Paringer R.A., Ushakova N.S., Kupriyanov A.V. Intellektual'nyj otbor priznakov dlya lokalizacii ob"ektov na izobrazheniyah glaznogo dna na osnove analiza cvetovyh podprostranstv. Informacionnye tekhnologii i nanotekhnologii (ITNT-2017). Samara, 2007. S. 1740–1746.
- Kociolek M., Materka A., Strzelecki M., Szczypiński P.M. Discrete wavelet transform-derived features for digital image texture analysis. Interational Conference on Signals and Electronic Systems. Lodz, 2001. V. 1. P. 163–168.
- Kim Dzh.-O., M'yuller Ch.U., Klekka U.R. i dr. Faktornyj, diskriminantnyj i klasternyj analiz / Pod red. I.S. Enyukova. M.: Finansy i statistika. 1989. 215 s.
- Il'yasova N.Yu., Paringer R.A. Issledovanie effektivnosti priznakov dlya diagnostiki sosudistoj patologii. Izvestiya Samarskogo nauchnogo centra Rossijskoj akademii nauk. 2015. T. 17. № 2. S. 1015–1020.