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Publications in Math-Net.Ru
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The “Planning – Modelling – Prediction” methodology for preoperative planning in trauma orthopaedics
Izv. Saratov Univ. Math. Mech. Inform., 24:3 (2024), 359–380
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Numerical analysis of the stress-strain state of osteotomies of the first metatarsal bone
Izv. Saratov Univ. Math. Mech. Inform., 23:4 (2023), 496–511
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The concept of medical decision support systems in surgery of the spinal pelvic complex
Izv. Saratov Univ. Math. Mech. Inform., 22:4 (2022), 517–535
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Construction of 3D solid vertebral models using convolutional neural networks
Izv. Saratov Univ. Math. Mech. Inform., 21:3 (2021), 368–378
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Constructing the dependence between the Young’s modulus value and the Hounsfield units of spongy tissue of human femoral heads
Izv. Saratov Univ. Math. Mech. Inform., 21:2 (2021), 182–193
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Using the Mask-RCNN convolutional neural network to automate the construction of two-dimensional solid vertebral models
Izv. Saratov Univ. Math. Mech. Inform., 20:4 (2020), 502–516
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Influence of convolution kernel and beam-hardening effect on the assessment of trabecular bone mineral density using quantitative computed tomography
Izv. Saratov Univ. Math. Mech. Inform., 20:2 (2020), 205–219
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Limited operator semigroups and issues of the convergence of the Bubnov–Galerkin method for one class of shallow shells nonlinear equations
Chebyshevskii Sb., 17:4 (2016), 110–123
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About numerical realization of the method of subsequent parameters perturbation for calculating a stress-strain state of shallow shells
Chebyshevskii Sb., 17:3 (2016), 28–37
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Numerical implementation of method of subsequent perturbation of parameters for computation of stress-strain state of a shell rigidly fixed on the boundaries
Izv. Saratov Univ. Math. Mech. Inform., 15:1 (2015), 74–79
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