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DOI: 10.14489/td.2026.04.pp.012-019
Ширшин А. В., Федоров А. В.
СПОСОБ И АЛГОРИТМ ОБРАБОТКИ ДАННЫХ РЕНТГЕНОВСКОЙ КОМПЬЮТЕРНОЙ ТОМОГРАФИИ ДЛЯ КОНТРОЛЯ СТРУКТУРЫ ИЗДЕЛИЙ ИЗ ПОЛИМЕРНЫХ КОМПОЗИЦИОННЫХ МАТЕРИАЛОВ
(с.12-19)
Аннотация. Предлагается и оценивается алгоритм автоматической сегментации изотекстурных зон изделий из полимерных композитных материалов (ПКМ) по данным рентгеновской компьютерной томографии (РКТ) на основе методов машинного обучения, текстурной фильтрации и объемного текстурного (радиомического) анализа, а также его программная реализация. Отмечено, что при использовании предлагаемого алгоритма достоверность разметки РКТ-данных повышается в сравнении с алгоритмом автоматизированной сегментации с 75,4 до 91,4 % при учете текстуры и с 86,7 до 92,9 % без учета текстуры (при разделении объект‒фон), а время, затрачиваемое на сегментацию (из расчета на 100 000 вокселей данных), снижается с 377,4 с для ручной сегментации до 13,4 с для автоматической. Применение разработанного алгоритма способно повысить точность сегментации изотекстурных зон изделий из ПКМ относительно существующих автоматизированных алгоритмов без значимого увеличения времени сегментации.
Ключевые слова: полимерные композитные материалы, аддитивные технологии, рентгеновская компьютерная томография, сегментация, машинное обучение, радиомика, простая линейная итеративная кластеризация.
Shirshin A. V., Fedorov A. V.
METHOD AND ALGORITHM FOR PROCESSING X-RAY COMPUTED TOMOGRAPHY DATA FOR AUTOMATIC SEGMENTATION OF POLYMER COMPOSITE MATERIALS PRODUCTS
(pp.12-19)
Abstract. Nowadays, additive technologies have made it possible to manufacture polymer composite materials (PCM) products with a programmable internal structure that determines the functional features of the products being created. To control the morphological structure of such products, X-ray computed tomography (XCT) is used, which allows obtaining data on the entire volume of the object being studied. At the same time, an important stage of control is the segmentation of zones of the same structure, the morphological features of which directly affect the quality of the product. Manual allocation of such zones has low productivity, and existing automation tools have a high margin of error in the case of allocation of various isotextural areas. In this paper, we propose and evaluate an algorithm for automatic segmentation of isotextural zones of PCM products based on XCT data based on machine learning methods, texture filtering and volumetric textual (radiomic) analysis, as well as its software implementation. It is noted that when using the proposed algorithm, the reliability of XCT data markup increases in comparison with the automated segmentation algorithm from 75.4 to 91.4 % with texture taken into account and from 86.7 to 92.9 % without texture (with object-background separation), and the time spent on segmentation (based on 100,000 voxels of data), decreases from 377.4 s for manual segmentation to 13.4 s for automatic segmentation. The application of the developed algorithm can improve the segmentation accuracy of the isotextural zones of PCM products relative to existing automated algorithms without significantly increasing the segmentation time.
Keywords: рolymer composite materials, additive technologies, X-ray computed tomography, segmentation, machine learning, radiomics, simple linear iterative clustering.
А. В. Ширшин, А. В. Федоров (ФГАОУ ВО «Национальный исследовательский университет ИТМО», Санкт-Петербург, Россия) E-mail:
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A.V. Shirshin, A.V. Fedorov (ITMO National Research University, Saint Petersburg, Russia) E-mail:
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2. Valueva, M. I., Evdokimov, A. A., Nacharkina, A. V., & Gubin, A. M. (2022). Polymer composite materials and technologies in the automotive industry. Proceedings of VIAM, (1), 53–65.
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4. Pires, L., Magalhães, F., & Moreira Pinto, A. (2022). New polymeric composites based on two-dimensional nanomaterials for biomedical applications. Polymers, 14(7), Article 1464.
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