3D Object Localization From 2D X-Ray Images for Surgical Alignment
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Solution Overview
Problem
Current surgical procedures for determining 3D relative positions and orientations between instruments and target objects in orthopedic and spinal surgery are challenging due to the reliance on intraoperative 2D imaging, which requires high spatial perception, is time-consuming, and involves high X-ray doses, especially in procedures like distal locking of intramedullary nails.
Innovation Solution
A system utilizing artificial intelligence, specifically deep morphing and neural networks, processes intraoperative 2D X-ray images to determine 3D representations and relative orientations without additional hardware, by classifying objects, determining geometric aspects, and providing instructions for C-arm adjustments based on X-ray imaging characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional iterative X-ray positioning is used to achieve accurate 3D alignment, then measurement precision is improved, but loss of time increases due to multiple iterations requiring 5-20 X-ray images
Solution Approach 1:
The system performs preliminary 3D reconstruction and virtual imaging before the actual surgical procedure. By pre-calculating the optimal positioning and visualizing it through augmented reality, the surgeon can directly implement the planned position without iterative adjustments, eliminating the time-consuming trial-and-error process while maintaining precision.
Solution Approach 2:
The system creates a virtual copy of the patient's anatomy through 3D reconstruction from preoperative scans. This digital twin is then used to simulate and plan the surgical procedure, allowing the surgeon to visualize and determine the exact 3D positioning before entering the operating room, thereby avoiding multiple X-ray iterations.
2Measurement precision
If multiple X-ray images are acquired for iterative positioning, then measurement precision is improved, but object-affected harmful factors increase due to higher X-ray dose exposure
Solution Approach 1:
All necessary 3D information is reconstructed from preoperative CT or MRI scans before surgery. The surgical plan is finalized in advance with precise 3D positioning determined through virtual imaging, eliminating the need for multiple intraoperative X-ray exposures and thereby reducing radiation dose to the patient.
Solution Approach 2:
The system introduces augmented reality visualization as an intermediary between the surgical plan and its execution. By overlaying virtual 3D models and guidance markers onto the surgeon's field of view, the system provides continuous positional feedback without requiring additional X-ray imaging, thus avoiding increased radiation exposure.
3Measurement precision
If high manual dexterity is required for precise instrument alignment in 2D X-ray images, then measurement precision is improved, but ease of operation deteriorates due to the complexity of spatial perception
Solution Approach 1:
The system transitions from 2D X-ray imaging to 3D augmented reality visualization. By reconstructing the patient's anatomy in three dimensions and overlaying it with virtual instrument models, the surgeon gains intuitive depth perception and spatial understanding, eliminating the cognitive burden of interpreting 2D projections and making precise alignment straightforward.
Solution Approach 2:
The augmented reality system provides real-time visual feedback by overlaying virtual instruments and anatomical structures onto the surgeon's actual field of view. This continuous feedback loop allows the surgeon to immediately see the consequences of instrument positioning adjustments, making precise alignment intuitive and reducing the skill threshold required for accurate surgery.
4Measurement precision
If additional hardware such as reference bodies or tracking systems is used to obtain 3D information, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system uses the patient's own preoperative imaging data (CT or MRI scans) to create a 3D model of their anatomy. This self-generated digital twin serves as the reference framework for surgical planning and augmented reality guidance, eliminating the need for external tracking markers, reference bodies, or complex registration hardware.
Solution Approach 2:
The augmented reality head-mounted display serves multiple functions: it displays the 3D reconstructed anatomy, overlays virtual surgical instruments, provides alignment guidance, and offers real-time feedback. This single device replaces what would otherwise require multiple separate hardware systems including tracking cameras, reference markers, and navigation consoles.
Data Source
AI summary
Systems and methods are provided for processing X-ray images, wherein the methods are implemented as a software program product executable on a processing unit of the systems. Generally, an X-ray image is received by the system, the X-ray image being a projection image of a first object and a second object. The first and second objects are classified and a respective 3D model of the objects is received. At the first object, a geometrical aspect like an axis or a line is determined, and at the second object, another geometrical aspect like a point is determined. Finally, a spatial relation between the first object and the second object is determined based on a 3D model of the first object, a 3D model of the second object, and the information that the point of the second object is located on the geometrical aspect of the first object.