Biplanar X-Ray 3D Reconstruction for Real-Time Surgical Navigation
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Solution Overview
Problem
Existing medical imaging technologies struggle to provide real-time, three-dimensional CT quality images of patient anatomy for surgical navigation, especially in minimally invasive procedures, due to challenges in reconstructing 3D volumes from limited 2D projections and aligning surgical instruments with patient coordinate systems.
Innovation Solution
A system combining optical and radiographic data uses precise pose estimation via camera calibration and deep learning techniques to reconstruct 3D volumes from biplanar X-ray images, aligning instrument coordinates with patient and volume coordinate systems, and correcting non-linear distortions, enabling accurate surgical navigation without exposing the patient's anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If fluoroscopic images are used for real-time visual assistance, then real-time imaging capability is improved, but three-dimensional anatomical information is lost
Solution Approach 1:
The patent transforms 2D fluoroscopic images into 3D anatomical representations by back-projecting multiple 2D projections into a 3D volume. The system acquires fluoroscopic images from multiple angles and uses iterative reconstruction algorithms to generate 3D volumetric data, enabling surgeons to visualize anatomical structures in three dimensions while maintaining real-time imaging capability.
2Loss of information
If computerized tomography is used for real-time three-dimensional image generation, then three-dimensional anatomical information is improved, but cost and time consumption increase
Solution Approach 1:
The patent uses inexpensive, portable fluoroscopic imaging equipment instead of expensive CT scanners. The system acquires multiple 2D fluoroscopic projections from different angles and reconstructs 3D volumes computationally, providing a cost-effective alternative that delivers real-time 3D anatomical information without the high costs and time requirements of traditional CT imaging.
3Device complexity
If traditional radiographic images are used, then equipment simplicity is improved, but real-time imaging and three-dimensional visualization are lost
Solution Approach 1:
The patent makes the fluoroscopic imaging system multi-functional by enabling it to perform both traditional 2D real-time imaging and 3D volumetric reconstruction. The same portable fluoroscopic equipment that provides real-time 2D visual guidance is also used to acquire multiple projections for 3D reconstruction, eliminating the need for separate complex imaging systems while delivering both 2D and 3D capabilities.
4Device complexity
If surgical navigation systems use visual position data only, then system simplicity is improved, but navigation accuracy for unexposed anatomy is reduced
Solution Approach 1:
The patent merges visual position tracking data with radiographic image data to create a comprehensive surgical navigation system. The system combines optical tracking of surgical instruments with 3D reconstructed anatomical volumes from fluoroscopic images, providing accurate navigation for both exposed and unexposed anatomy while maintaining relative system simplicity through integrated software processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient, accurate, and real-time generation of 3D CT quality images, enhancing surgical navigation by precisely tracking surgical instruments within the reconstructed 3D volume, improving procedural accuracy and safety.
Implementation Method 1
Each of the two X-ray projections is back projected into a separate three-dimensional volume using the Radon transform
Implementation Method 2
capturing a first and a second biplanar set of radiographic images using an X-ray imaging system
Data Source
AI summary
A system and method combine optical and radiographic data to enhance imaging capabilities. Specifically, the system combines visually obtained patient pose position information and radiographic image information to facilitate calibrated surgical navigation. A reconstruction of a 3D CT volume is generated from biplanar X-ray projections which are back projected into two separate volumes and then concatenated into a single volume along a new dimension and passed through a pretrained deep learning model to decode the concatenated volume into a single 3D volume.