Department of Neuroscience, Max Rubner Institute, Hermann-Weigmann Street, Kiel, Germany
Review
Analysis of Large-Scale MRI Spine Data Using a Deep Learning Approach
Author(s): Alcantara Ortigoza*
The German National Cohort (GNC) has the potential to provide standardized biometric reference values for intervertebral discs (VD), vertebral
bodies (VB) and the spinal canal (SC) thanks to its uniform MRI datasets covering the entire spine. Artificial intelligence (AI) tools are required
to manage such massive amounts of big data. An AI software tool for analyzing spine MRI and generating normative standard values will be
presented in this manuscript. Age, sex and height parameters were evenly distributed among the 330 representative GNC MRI datasets that were
chosen at random. A 3D U-Net was used to train, validate and test an AI algorithm. In the end, the entire dataset (n = 10,215) was looked at by the
machine learning algorithm. An AI-based algorithm was used to successfully segment and analyze VB, VD and SC. For the purpose of analyzing
spine MRI data an.. Read More»
DOI:
10.37421/2165-7939.2022.11.565
Journal of Spine received 2022 citations as per Google Scholar report