Multi-perspective region-based CNNs for vertebrae labeling in intraoperative long-length images.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 3, 2022

Abstract

PURPOSE: Effective aggregation of intraoperative x-ray images that capture the patient anatomy from multiple view-angles has the potential to enable and improve automated image analysis that can be readily performed during surgery. We present multi-perspective region-based neural networks that leverage knowledge of the imaging geometry for automatic vertebrae labeling in Long-Film images - a novel tomographic imaging modality with an extended field-of-view for spine imaging.

Authors

  • Y Huang
    Research Information Solutions and Innovations , Columbus, OH.
  • C K Jones
    Animal Sciences and Industry, Kansas State University, Manhattan, KS.
  • X Zhang
    Agricultural and Rural Bureau of Hanjiang District, Yangzhou 225100, China.
  • A Johnston
    Life Whisperer Diagnostics, Presagen Pty Ltd., Adelaide, SA 5000, Australia.
  • S Waktola
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, United States.
  • N Aygun
    Department of Radiology, Johns Hopkins Medicine, Baltimore MD, United States.
  • T F Witham
    Department of Neurosurgery, Johns Hopkins Medicine, Baltimore MD, United States.
  • A Bydon
    Department of Neurosurgery, Johns Hopkins Medicine, Baltimore MD, United States.
  • N Theodore
    Department of Neurosurgery, Johns Hopkins Medicine, Baltimore MD, United States.
  • P A Helm
    Medtronic, Littleton MA, United States.
  • J H Siewerdsen
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, United States; Department of Computer Science, Johns Hopkins University, Baltimore MD, United States; Department of Radiology, Johns Hopkins Medicine, Baltimore MD, United States; Department of Neurosurgery, Johns Hopkins Medicine, Baltimore MD, United States; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston TX, United States.
  • A Uneri
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, United States. Electronic address: ali.uneri@jhu.edu.

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