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Updated: Jun 17, 2025

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Published on: August 6, 2019

A review: artificial intelligence in image-guided spinal surgery.

Jiahang Zeng^1,2, Qiang Fu²

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

Expert Review of Medical Devices

|August 8, 2024

Summary

This summary is machine-generated.

Artificial intelligence (AI) enhances image-guided spinal surgery, improving outcomes. Further data collection is crucial for ensuring the safety of AI-augmented surgical procedures.

Keywords:

Image-guided spinal surgery intra-operative registration pre-operative planning spine image segmentation surgical navigation three-dimensional reconstruction

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Last Updated: Jun 17, 2025

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Cone Beam Intraoperative Computed Tomography-based Image Guidance for Minimally Invasive Transforaminal Interbody Fusion

Published on: August 6, 2019

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Published on: May 11, 2020

Pedicle Screw Placement Using an Augmented Reality Head-Mounted Display in a Porcine Model

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Published on: May 24, 2024

Area of Science:

Neurosurgery
Medical Imaging
Artificial Intelligence

Background:

Spinal surgery requires high technical skill due to complex anatomy and procedures.
Image-guided spinal surgery improves lesion visualization, reduces operation time, and enhances outcomes.

Purpose of the Study:

To review advancements in deep learning and AI for image-guided spinal surgery.
To offer guidance for surgeons, engineers, and researchers in this field.

Main Methods:

Review of current literature on AI and deep learning in image-guided spinal surgery.
Analysis of AI's impact on surgical outcomes and procedural safety.

Main Results:

AI-augmented image-guided spinal surgery demonstrates superior performance compared to traditional methods.
Enhanced visualization and reduced operation times are key benefits.

Conclusions:

AI integration in spinal surgery promises to boost surgeon proficiency and patient outcomes.
Expanding datasets is essential for validating and ensuring the safety of AI in surgical procedures.