X-ray Imaging Algorithm for Positioning Variance Estimation
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Solution Overview
Problem
X-ray imaging systems face reduced diagnostic data resolution and artifacts due to positioning variances in imaging apparatus components, particularly in two-dimensional and three-dimensional image reconstructions, which are challenging to accurately estimate without high-cost, rigid, and complex stands.
Innovation Solution
A computer-implemented method generates annotated training data by simulating x-ray recordings with predetermined positioning variances, allowing an algorithm to be trained for estimating these variances, using machine learning techniques like neural networks to predict and correct positioning inaccuracies in real-time x-ray recordings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stands with very high rigidity and drive components with very low tolerances are used, then positioning accuracy is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent replaces the mechanical solution (rigid stands with low-tolerance components) with a computational approach. An algorithm estimates positioning variances by analyzing deviations between actual and target positioning data from x-ray recordings, eliminating the need for mechanically complex stands while achieving the same positioning accuracy.
Solution Approach 2:
The patent introduces an algorithm as an intermediary between the imaging apparatus and the image reconstruction process. This algorithm processes positioning data and estimates variances, serving as a software mediator that compensates for positioning inaccuracies without requiring hardware modifications to the stand.
2Measurement precision
If stands with very high rigidity are used, then positioning accuracy is improved, but weight increases
Solution Approach 1:
The patent substitutes heavy mechanical rigidification measures with a lightweight computational algorithm. The algorithm runs on existing system hardware to estimate and compensate for positioning variances, achieving high positioning accuracy without adding significant weight to the imaging system.
3Loss of information
If image recordings are processed with subtraction methods or three-dimensional reconstruction, then diagnostic information is improved, but artifacts and blurring increase due to positioning variances
Solution Approach 1:
The patent applies preliminary action by estimating positioning variances before the image reconstruction or subtraction process. The algorithm analyzes positioning data from multiple x-ray recordings and pre-calculates variance estimates, which are then used to correct or compensate for positioning errors during subsequent image processing, preventing artifacts and blurring in the final diagnostic images.
Solution Approach 2:
The patent implements feedback by using actual positioning data from x-ray recordings to estimate variances, which are then fed back into the image reconstruction process. This closed-loop approach allows the system to continuously adjust and compensate for positioning errors, improving diagnostic image quality while reducing artifacts.
Data Source
AI summary
A computer-implemented method for generating training data for training an algorithm for estimating positioning variances in an imaging apparatus of an x-ray imaging system is provided. The method includes predetermining target positioning data for the imaging apparatus and calculating faulty positioning data, wherein the faulty positioning data deviates from the target positioning data by at least one predetermined positioning variance. An imaging method is simulated, in order to generate two or more simulated x-ray recordings, wherein a positioning of the imaging apparatus is simulated in accordance with the faulty positioning data. An annotated training data record is generated and stored, wherein the training data record contains two or more simulated x-ray recordings and at least one positioning variance as an annotation of the two or more simulated x-ray recordings.