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Related Experiment Video

Updated: Oct 30, 2025

Neuronavigated Focalized Transcranial Direct Current Stimulation Administered During Functional Magnetic Resonance Imaging
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DeepNavNet: Automated Landmark Localization for Neuronavigation.

Christine A Edwards1,2,3, Abhinav Goyal2,4, Aaron E Rusheen2,4

  • 1School of Engineering, Deakin University, Geelong, VIC, Australia.

Frontiers in Neuroscience
|July 5, 2021
PubMed
Summary

A new deep learning pipeline, DeepNavNet, automatically locates key brain landmarks (anterior and posterior commissures) in MRI scans with submillimeter accuracy. This advances neurosurgical precision by eliminating manual steps and atlas reliance.

Keywords:
deep brain stimulationdeep learninghuman-machine teaminglandmark localizationneuroimagingneuronavigationneurosurgery planning

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Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Functional neurosurgery relies on precise image-guided navigation.
  • Current methods use atlas-image registration for deep brain structure targeting, which is imprecise and time-consuming.
  • Manual identification of anatomical landmarks like the anterior and posterior commissures (AC and PC) is prone to human error.

Purpose of the Study:

  • To develop a deep learning pipeline for accurate and automatic localization of AC and PC landmarks in MRI volumes.
  • To improve the efficiency and precision of neurosurgical planning and execution.

Main Methods:

  • A novel deep learning pipeline, DeepNavNet, was created to regress MRI scans to heatmap volumes.
  • The pipeline automatically identifies the 3D coordinates of AC and PC landmarks with submillimeter accuracy.
  • The model was trained and validated on 1128 manually labeled MRI volumes and tested on 311 volumes.

Main Results:

  • DeepNavNet achieved a mean 3D localization error of 0.79 ± 0.33 mm for AC and 0.78 ± 0.33 mm for PC.
  • The model significantly outperformed a baseline method in localization accuracy.
  • The pipeline demonstrated consistent and automatic landmark detection without requiring an atlas.

Conclusions:

  • DeepNavNet offers submillimeter accuracy for AC and PC landmark localization in MRI.
  • This automated approach enhances neurosurgical planning and execution by improving accuracy and efficiency.
  • The pipeline represents a significant advancement in image-guided neurosurgery.