Paper
4 October 2023 Computed tomography images preliminary processing for their analysis by artificial intelligence methods
Nataliia I. Limanova, Sergey V. Palmov, Dmitry A. Morozov
Author Affiliations +
Proceedings Volume 12743, Optical Technologies for Telecommunications 2022; 127430Y (2023) https://doi.org/10.1117/12.2680857
Event: Optical Technologies for Telecommunications 2022, 2022, Ufa, Russian Federation
Abstract
In this paper we consider method, proposed by the authors, for pre-processing X-ray images based on the convolutional neural network. Multilayer computed tomography scans of the lungs are ubiquitous, used to detect pathology, such as covid-19 diseases. The proposed method consists of computed tomography lung image segmentation, the volume of interest localization at these scans, distinguishing between denser structures, such as bones, and less dense ones, such as blood vessels. A comparison of the pathological formations classification quality was made on images with different degrees of preprocessing on large data sets. Image Classifier software was developed for demonstration of x-rays preliminary processing opportunities in the context of their class association forecasting. The developed software showed quite good results. Maximum value of the average probability reached 77.5%. The number of epochs required to achieve the specified quality level is four.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nataliia I. Limanova, Sergey V. Palmov, and Dmitry A. Morozov "Computed tomography images preliminary processing for their analysis by artificial intelligence methods", Proc. SPIE 12743, Optical Technologies for Telecommunications 2022, 127430Y (4 October 2023); https://doi.org/10.1117/12.2680857
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KEYWORDS
Lung

X-ray imaging

X-rays

Image segmentation

Tunable filters

Image processing

Tissues

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