Sergey Golushko

Novosibirsk State University

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ЕЛ

Е. Л. Амелина

Novosibirsk State University

M. E. Amelin

Federal Neurosurgical Center Novosibirsk

Bair Tuchinov

Novosibirsk State University

A. Yu. Letyagin

Institute of Cytology and Genetics

V. A. Belyaev

Kurchatov Institute

Vladimir Groza

Novosibirsk State University

Evgeniy Pavlovskiy

Novosibirsk State University

ЛС

Л. С. Брындин

Novosibirsk State University

Nikolay Tolstokulakov

Novosibirsk State University

Arseniy Gorynin

Novosibirsk State University

Cooperative Institutions

Novosibirsk State University

Russian Academy of Sciences

Institute of Computational Technologies

Siberian Branch of the Russian Academy of Sciences

Federal Neurosurgical Center Novosibirsk

Institute of Cytology and Genetics

Institute of Theoretical and Applied Mechanics

Ministry of Health of the Russian Federation

Kurchatov Institute

Development Agency of Serbia

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Отчет за 2010 г. Математическое моделирование в задачах анализа, проектирования и оптимизации технических систем и технологических процессов

Sergey Golushko О.Ф. Воропаева А.В. Юрченко В.Н. Гребенев Ю.Н. Григорьев

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STUDY OF RESTRAINED TORSION OF THIN-WALLED OPEN-SECTION BEAMS USING THE ASYMPTOTIC SPLITTING METHOD

Journal of Applied Mechanics and Technical Physics (2024)

Arseniy Gorynin Г. Л. Горынин Sergey Golushko

Section (typography)

10.1134/s002189442403012x

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Mathematical modeling and numerical calculation of composite structures

Journal of Physics Conference Series (2017)

Sergey Golushko

The report is devoted to modeling the properties of composite materials. Two major approaches are considered: phenomenological and structural [1]. Within the framework of the first approach reinforced materials are modeled as homogeneous anisotropic medium with efficient physical and mechanical properties. In this case mechanical parameters of the material are determined basing on experimental data. In a structural approach, physical and mechanical parameters of the composite are expressed in terms of the parameters of its components and design of reinforcement that open up opportunities for improvement of the properties of composite structures. The mathematical relations describing the nonlinear elastic three-point bending of isotropic and reinforced beams with account of different strength and stiffness behavior in tension and compression are obtained. An algorithm for numerical solution of corresponding boundary-value problems is proposed and implemented. Results of numerical modeling have been compared to acquired data for polymer matrix and structural carbon fiber reinforced plastics.

Tension (geology)

10.1088/1742-6596/894/1/012021

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Citations (1)

New versions of the least-squares collocation method for solving differential and integral equations

Journal of Physics Conference Series (2021)

В. П. Шапеев Sergey Golushko V. A. Belyaev Л. С. Брындин P. L. Kirillov

Abstract This paper describes new versions of the least-squares collocation method for solving differential and integral equations. A p-version of the method has been proposed and implemented to solve nonlinear systems of partial differential equations. The stationary Navier-Stokes equations are used as an example. A hp-version of the method has been implemented for the numerical solution of the Fredholm integral equations of the second kind in the one-and two-dimensional cases. This paper shows that approximate solutions obtained by various versions of the least-squares collocation method converge with a high order and agree with analytical solutions of test problems with a high degree of accuracy.

Orthogonal collocation

Collocation (remote sensing)

Least-squares function approximation

10.1088/1742-6596/1715/1/012031

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Citations (4)

Data Preprocessing Via Compositions Multi-Channel MRI Images to Improve Brain Tumor Segmentation

Nikolay Tolstokulakov Evgeniy Pavlovskiy Bair Tuchinov Е. Л. Амелина M. E. Amelin

Magnetic resonance imaging (MRI) stays one of the most essential noninvasive methods for brain diagnostics. It allows obtaining the detailed 3D image of the brain, including various types of soft tissues. In this paper, we compare the influence of the multichannel data composition approach on the model's performance. We consider the binary brain tumor segmentation problem evaluating the Dice, Recall and Precision metrics. One common way to process the medical images with the use of neural networks is to use 2D slices as the input. In contrast to the RGB images, there are plenty of methods of how to combine the multi-channel MRI data structure into the common format for ML-based algorithms. After evaluating several possible combinations we demonstrate the most performance improvement by 6–7% in Dice & Recall metrics using the pseudo-RGB approach.

10.1109/isbiworkshops50223.2020.9153416

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Citations (3)

Journal of Applied Mechanics and Technical Physics (2002)

Sergey Golushko A. V. Yurchenko

Orthogonalization

10.1023/a:1014722213849

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Citations (2)

Artificial Intelligence for Imaging Diagnostics in Neurosurgery

2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) (2019)

A. Yu. Letyagin Liana O. Degtyareva Sergey Golushko Jamil Rzaev M. E. Amelin

Improving the accuracy and timeliness of medical imaging in everyday clinical neurosurgery practice is an urgent problem for the health care of all countries. This problem will be solved with the help of artificial intelligence (AI). By performing the search and contouring of "suspicious" pathological objects, making automatic measurements on 3D medical images (MRI, CT), formalizing quantitative indicators and compiling medical statistical reports, AI can solve diagnostic problems in radiology and medical imaging. The effect of introducing AI will be at least a more accurate and quick interpretation of images, implemented through a set of decision-making tools for medical specialists.

10.1109/sibircon48586.2019.8958201

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Citations (5)

New Possibilities and Applications of the Least Squares Collocation Method

EPJ Web of Conferences (2018)

Vasiliy Pavlovich Shapeev V. A. Belyaev Sergey Golushko Semyon Idimeshev

Least squares collocation method (LSC) is a versatile numerical method for solving boundary value problems for PDE. The present article demonstrates the abilities of LSC to solve various problems – in particular, calculations of bending of isotropic irregular shaped plates and multi-layered anisotropic plates. In order to achieve higher accuracy, new versions of the method utilize high-degree polynomial spaces. The numerical experiments demonstrate high accuracy of the solutions.

Collocation (remote sensing)

Moving least squares

Least-squares function approximation

10.1051/epjconf/201817301012

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Citations (11)

A Cubic Version of the Least-Squares Collocation Method and Its Application to the Calculation of Plate Bending

Journal of Applied and Industrial Mathematics (2024)

Sergey Golushko Л. С. Брындин V. A. Belyaev Arseniy Gorynin

Collocation (remote sensing)

Moving least squares

Least-squares function approximation