3D Reconstruction from Multi-Pose C-Arm X-Rays Without Sensors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional manual C-arm imaging systems lack the capability to reconstruct three-dimensional structures due to the lack of depth information in two-dimensional fluoro-images, making it difficult to determine the relative pose of surgical tools relative to targets, necessitating guesswork and limiting the use of advanced image reconstruction methods.
Innovation Solution
A system and method for reconstructing three-dimensional structures from a series of two-dimensional X-ray images taken at different poses using a loss function to minimize the difference between estimated and actual structures, without requiring additional positional sensors or fiducial markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional manual C-arm systems are used to take X-ray images, then the system is simple and easy to operate, but the system cannot reconstruct three-dimensional structures due to lack of depth information
Solution Approach 1:
The patent introduces an intermediary computational process (loss function minimization) that mediates between the simple manual C-arm system and the desired 3D reconstruction capability. The system uses software-based image processing and optimization algorithms to extract depth information from 2D images without adding complex hardware sensors or markers, thus resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent replaces mechanical measurement systems (positional sensors, fiducial markers) with a computational approach using loss function minimization. Instead of using physical devices to measure and track position, the system uses mathematical optimization to infer 3D structure from 2D images, substituting mechanical complexity with computational processing
2Measurement precision
If additional positional sensors or fiducial markers are added to enable 3D reconstruction, then depth information can be obtained, but the device complexity and cost increase
Solution Approach 1:
The patent enables the manual C-arm system to perform 3D reconstruction using its own existing 2D imaging capability. The system processes the images it already captures through loss function minimization to self-generate depth information, eliminating the need for external sensors or markers and maintaining operational simplicity
3Measurement precision
If manual C-arm systems are used without 3D reconstruction capability, then the system is simple to operate, but surgical tool localization requires guesswork and is imprecise
Solution Approach 1:
The patent introduces an intermediary computational layer (loss function and optimization algorithm) that transforms ordinary 2D X-ray images into accurate 3D structural information. This intermediary process enables precise surgical tool localization by providing depth data that was previously unavailable, while keeping the underlying hardware simple and easy to operate
Data Source
AI summary
Three-dimensional structure reconstruction systems and related methods are disclosed. In some examples, a three-dimensional structure reconstruction system may include at least one processor configured to: receive a plurality of X-ray images of an object, wherein the plurality of X-ray images are taken at a plurality of poses relative to the object; determine a loss function based on: an estimated three-dimensional structure, and the plurality of X-ray images of the object; and determine a reconstructed three-dimensional structure by minimizing the loss function. In some examples, at least one non-transitory computer-readable medium may have instructions thereon that, when executed by at least one processor, perform a method for three-dimensional structure reconstruction. In some examples, a method may include receiving X-ray images of an object; determining a loss function based on: an estimated three-dimensional structure, and the X-ray images; and determining a reconstructed three-dimensional structure by minimizing the loss function.