Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Workshop on Photogrammetric and Computer Vision Techniques for Video Surveillance, Biometrics and Biomedicine, PSBB 2021

Год издания: 2021

Ключевые слова: color-coded contrasting, ct image, lung pathology from covid-19, prognosis of outcomes, pulmonary fibrosis, texture image analysis

Аннотация: In recent years computed tomography of the lungs has been the most common diagnostic procedure aimed at detection of the pathological changes associated with COVID-19. The study is aimed at the use of the developed algorithmic support in combination with texture (geometric) analysis to highlight a number of indicators characterizing the clinical state of the object of interest. Processing is aimed at the solution of a number of diagnostic tasks such as highlighting and contrasting the objects of interest, taking into account the color coding. Further, an assessment is performed according to the appropriate criteria in order to find out the nature of the changes and increase both the visualization of pathological changes and the accuracy of the X-ray diagnostic report. For these purposes, it is proposed to use preprocessing algorithms for a series of images in dynamics. Segmentation of the lungs and areas of possible pathology are performed using wavelet transform and Otsu threshold value. Delta-maps and maps obtained using Shearlet transform with contrasting color coding are used as a means of visualization and selection of features (markers). The analysis of the experimental and clinical material carried out in the work shows the effectiveness of the proposed combination of methods for studying of the variability of the internal geometric features (markers) of the object of interest in the images. © Authors 2021. CC BY 4.0 License.

Журнал: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Выпуск журнала: Vol. 54, Is. 2/W1

Номера страниц: 99-105

ISSN журнала: 16821750

Издатель: International Society for Photogrammetry and Remote Sensing

• Kents A.S. (Federal State-Financed Institution, Federal Siberian Research Clinical Centre, Federal Medical Biological Agency, 26 Kolomenskaya st, Krasnoyarsk, 660037, Russian Federation)
• Hamad Yu.A. (Institute of Space and Information Technologies, Siberian Federal University, 79 Svobodny st, Krasnoyarsk, 660041, Russian Federation)
• Simonov K.V. (Institute of Computational Modelling, The SB, RAS, 50/44 Akademgorodok, Krasnoyarsk, 660036, Russian Federation)
• Zotin A.G. (Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy ave, Krasnoyarsk, 660037, Russian Federation)

• Scopus