Machine learning for image analysis in the cervical spine: Systematic review of the available models and methods

C M W Goedmakers; L M Pereboom; J W Schoones; M L de Leeuw den Bouter; R F Remis; M Staring; C L A Vleggeert-Lankamp

doi:10.1016/j.bas.2022.101666

Machine learning for image analysis in the cervical spine: Systematic review of the available models and methods

Brain Spine. 2022 Nov 14:2:101666. doi: 10.1016/j.bas.2022.101666. eCollection 2022.

Authors

C M W Goedmakers^{1

2}, L M Pereboom³, J W Schoones⁴, M L de Leeuw den Bouter⁵, R F Remis⁶, M Staring^{7

8}, C L A Vleggeert-Lankamp^{1

9

10}

Affiliations

¹ Department of Neurosurgery, Leiden University Medical Center, Leiden, the Netherlands.
² Computational Neuroscience Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
³ Faculty of Mechanical, Maritime and Materials Engineering (3mE), Delft University of Technology, Delft, the Netherlands.
⁴ Walaeus Library, Leiden University Medical Center, Leiden, the Netherlands.
⁵ Delft Institute of Applied Mathematics, Department of Numerical Analysis, Delft University of Technology, Delft, the Netherlands.
⁶ Circuits and Systems Group, Microelectronics Department, Delft University of Technology, Delft, the Netherlands.
⁷ Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
⁸ Intelligent Systems Department, Delft University of Technology, Delft, the Netherlands.
⁹ Department of Neurosurgery Haaglanden Medical Centre and HAGA Teaching Hospitals, The Hague, the Netherlands.
¹⁰ Department of Neurosurgery, Spaarne Gasthuis Haarlem/Hoofddorp, the Netherlands.

Abstract

•Neural network approaches show the most potential for automated image analysis of thecervical spine.•Fully automatic convolutional neural network (CNN) models are promising Deep Learning methods for segmentation.•In cervical spine analysis, the biomechanical features are most often studied using finiteelement models.•The application of artificial neural networks and support vector machine models looks promising for classification purposes.•This article provides an overview of the methods for research on computer aided imaging diagnostics of the cervical spine.

Keywords: Cervical spine; Computer aided diagnostics; Image analysis; Machine learning; Radiological imaging.

Publication types

Review