X-ray Image Quality Assessment via Simulated Positioning Data

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Solution Overview

Problem

Assessing the quality of medical images obtained from X-ray systems is challenging, as it depends on the accurate positioning of the X-ray source and detector, and existing methods often rely on trial and error, leading to inefficiencies and potential radiation exposure.

Innovation Solution

A computer-implemented method that generates multiple positioning data sets with varying parameters, obtains corresponding medical images, and assesses their quality by comparing measured quality metrics with predefined thresholds, iteratively adjusting the positioning data sets until a satisfactory image quality is achieved.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If multiple positioning data sets are generated and multiple medical images are obtained to assess image quality, then image quality assessment accuracy is improved, but radiation exposure increases

Engineering Contradiction:

Improveimage quality assessment accuracyVSAvoidradiation exposure

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary quality assessment using simulated image data before actual imaging. Positioning data sets are generated and assessed in advance using simulation, allowing the system to pre-select optimal positioning parameters that will yield adequate image quality, thereby avoiding unnecessary radiation exposure from trial-and-error imaging attempts.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates simulated copies of medical images based on positioning data sets before obtaining actual medical images. These simulated images allow quality assessment to be performed on virtual data, enabling the selection of optimal positioning parameters without exposing the patient to radiation from multiple actual imaging trials.

Inventive Principle:

Principle #26Copying

2Reliability

If trial and error method is used to assess image quality, then image quality can be evaluated, but time consumption and inefficiency increase

Engineering Contradiction:

Improveimage quality evaluationVSAvoidtime consumption

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system implements automated feedback loops where image quality metrics are continuously assessed and compared against predefined thresholds. The system automatically adjusts positioning parameters based on quality assessment results, eliminating manual trial-and-error processes and significantly reducing time consumption while maintaining reliable quality evaluation.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system systematically varies positioning parameters (such as source-to-detector distance, detector angle, source angle) and automatically assesses the impact on image quality metrics. This structured parameter exploration replaces inefficient manual trial-and-error with an automated process that quickly identifies optimal positioning parameters.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If manual assessment of image quality is performed, then quality evaluation can be conducted, but operator dependency and subjectivity increase

Engineering Contradiction:

Improvequality assessment capabilityVSAvoidoperator dependency

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs self-assessment of image quality using automated algorithms that evaluate positioning accuracy and image quality metrics without human intervention. The system independently generates positioning data sets, obtains medical images, assesses quality against predefined criteria, and determines whether additional imaging is needed, eliminating operator dependency and subjectivity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual visual assessment by operators with automated computational analysis. Image quality metrics are calculated and evaluated using computer algorithms that objectively compare actual images against ideal positioning criteria, eliminating subjectivity and operator variability inherent in manual assessment.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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 method enhances the quality of medical images, reduces radiation exposure by minimizing the number of imaging trials, increases efficiency, and simplifies the imaging process by providing a systematic approach to achieving adequate image quality.

Implementation Method 1

Radiation based medical imaging such as X-ray imaging or CT-imaging

Methodology Applied

Scientific EffectX-ray radiation: X-Ray

Data Source

PatentUS20250131556A1autofocus

Publication Date: 2025.04.24 BRAINLAB AG

AI summary

Provided is a computer-implemented method for assessing a medical image of an object imaged with an X-ray system. The method proposes to generate one or more positioning data sets, which differ in at least one positioning parameter. The X-ray system images medical images of the object with the one or more positioning data sets. The obtained medical images were assessed by measuring a quality measure in the medical images and comparing the measured quality measures with an evaluation criterion. A positive assessed medical image with the corresponding positioning data is then provided for further processing.