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Proceedings Paper

Application of artificial neural network technologies to vertebral segmentation according on CT data
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Paper Abstract

The method of 2D segmentation of vertebrae based on computer tomography data (DICOM files) in sagittal projection using artificial neural network Mask-RCNNN is considered in this study. The effectiveness of network recognition was compared with manual segmentation performed by a professional physician. The comparison of accuracy between the neural network and manual segmentation was evaluated using the Sørens coefficient. The result of automatic 2D segmentation has been tested by professional physicians. The application of the method makes it possible to significantly speed up the process of modeling bone structures of the spine in 2D mode to solve the problems of biomechanics.

Paper Details

Date Published: 21 February 2020
PDF: 4 pages
Proc. SPIE 11229, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVIII, 112291Y (21 February 2020); doi: 10.1117/12.2545001
Show Author Affiliations
Alexander S. Beskrovny, Saratov State Univ. (Russian Federation)
Alexei V. Makhankov, Saratov State Univ. (Russian Federation)
Leonid V. Bessonov, Saratov State Univ. (Russian Federation)
Maksim O. Lemeshkin, Saratov State Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 11229:
Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVIII
Anita Mahadevan-Jansen, Editor(s)

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