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

Alexander S. Beskrovny; Alexei V. Makhankov; Leonid V. Bessonov; Maksim O. Lemeshkin

doi:10.1117/12.2545001

21 February 2020 Application of artificial neural network technologies to vertebral segmentation according on CT data

Alexander S. Beskrovny, Alexei V. Makhankov, Leonid V. Bessonov, Maksim O. Lemeshkin

Proceedings Volume 11229, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVIII; 112291Y (2020) https://doi.org/10.1117/12.2545001
Event: SPIE BiOS, 2020, San Francisco, California, United States

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.

Citation Download Citation

Alexander S. Beskrovny, Alexei V. Makhankov, Leonid V. Bessonov, and Maksim O. Lemeshkin "Application of artificial neural network technologies to vertebral segmentation according on CT data", Proc. SPIE 11229, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XVIII, 112291Y (21 February 2020); https://doi.org/10.1117/12.2545001

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KEYWORDS

Image segmentation

Neural networks

Artificial neural networks

Spine

Computed tomography

Medical imaging

Process modeling

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