Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Beskrovny A. S., Bessonov L. V., Ivanov D. V., Zolotov V. S., Sidorenko D. A., Kirillova I. V., Kossovich L. Y. Construction of 3D solid vertebral models using convolutional neural networks. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2021, vol. 21, iss. 3, pp. 368-378. DOI: 10.18500/1816-9791-2021-21-3-368-378, EDN: XOVJRW

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
31.08.2021
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Russian
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Article
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519.688
EDN: 
XOVJRW

Construction of 3D solid vertebral models using convolutional neural networks

Autors: 
Beskrovny Alexander S., Saratov State University
Bessonov Leonid Valentinovich, Saratov State University
Ivanov Dmitry V., Saratov State University
Zolotov Vladislav S., Saratov State University
Sidorenko Dmitry A., Saratov State University
Kirillova Irina V., Saratov State University
Kossovich Leonid Yurevich, Saratov State University
Abstract: 

The quality of solving the problem of biomechanical modeling largely depends on the created solid-state model of the biological object under study. Building a model based on computed tomography data for a particular patient is possible both in manual mode (software packages for processing medical images) and using automated tools for building a model (image segmentation), which significantly speeds up the process of creating a solid model, in contrast to the manual mode. The complexity of the automated approach lies in the reconstruction of a segmented image into a solid model suitable for biomechanical modeling. As a rule, automatic segmentation is hampered by the presence of anatomical pathologies, noise, and the presence of implants in the images of a digital study. The article proposes a method for creating a solid model from a point cloud obtained from computed tomography data using convolutional neural networks SpatialConfiguration-Net and U-Net. The results of the implementation were applied in the development of the "Module of Solid Models'', which is included in the prototype of the medical decision support system SmartPlan Ortho 3D, which is being developed at Saratov State University within the framework of the project of the Foundation for Advanced Research. The system is included in the register of Russian software.

Acknowledgments: 
The work was supported by the Russian Foundation for Advanced Research (agreement No. 6/130/2018-2021 from 01.08.2018).
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Received: 
15.03.2021
Accepted: 
29.04.2021
Published: 
31.08.2021