Self-Supervised Feature Detection and 3D Reconstruction for Real-Time Neuroendoscopic Guidance.

Journal: IEEE transactions on bio-medical engineering
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: Transventricular approach to deep-brain targets offers direct visualization but also imparts deformation that challenges accurate neuronavigation. 3D reconstruction and registration of the endoscopic view could provide up-to-date, real-time guidance. We develop and evaluate a self-supervised feature detection method for 3D reconstruction and navigation in neuroendoscopy.

Authors

  • Prasad Vagdargi
    Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.
  • Ali Uneri
    Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD, USA.
  • Stephen Z Liu
  • Craig K Jones
    2Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore; and.
  • Alejandro Sisniega
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
  • Junghoon Lee
    Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Patrick A Helm
    Medtronic Plc., Littleton, Massachusetts, USA.
  • Ryan P Lee
  • Mark G Luciano
  • Gregory D Hager
    Department of Computer Science, The Johns Hopkins University, 3400 N. Charles St., Malone Hall Room 340, Baltimore, MD, 21218, USA.
  • Jeffrey H Siewerdsen
    Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD, USA.

Keywords

External Resources

Popular Topics
Recent Journals