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Journal of Spine

ISSN: 2165-7939

Open Access

Alcantara Ortigoza

Department of Neuroscience, Max Rubner Institute, Hermann-Weigmann Street, Kiel, Germany

Publications
  • 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

    Abstract HTML PDF

Google Scholar citation report
Citations: 2022

Journal of Spine received 2022 citations as per Google Scholar report

Journal of Spine peer review process verified at publons

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