X-Ray Detector Characterization for Synthetic Image Evaluation
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Solution Overview
Problem
Existing methods for evaluating X-ray detector image quality are time-consuming and unreliable, often leading to inaccurate assessments of detector quality and potential image artifacts, which can result in suboptimal performance or rejection of detectors with sufficient quality.
Innovation Solution
A computer-implemented method using a trained algorithm, particularly a generative artificial intelligence model, to generate synthetic image data based on characterization data of detector modules, allowing early prediction of image quality and potential artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image testing methods are used to evaluate X-ray detector quality, then measurement reliability is improved, but testing time increases significantly
Solution Approach 1:
The patent applies preliminary action by performing characterization measurements on individual detector modules during manufacturing before final assembly. This early-stage data collection enables subsequent rapid quality assessment without requiring time-consuming full-system image testing, thus resolving the contradiction between reliability and testing time.
Solution Approach 2:
The patent creates a digital twin or virtual model of the detector system using characterization data from individual modules. This virtual representation allows quality assessment to be performed on the copied model rather than requiring physical image testing of the actual assembled detector, significantly reducing testing time while maintaining assessment reliability.
2Measurement precision
If comprehensive image tests are performed on assembled detectors, then detection precision of artifacts is improved, but production efficiency decreases
Solution Approach 1:
The patent segments the quality assessment process into two parts: (1) characterization measurements on individual detector modules during manufacturing, and (2) rapid evaluation using stored characterization data. This segmentation allows comprehensive artifact detection precision to be maintained through detailed module-level measurements while improving production efficiency by avoiding repeated full-system testing.
Solution Approach 2:
By performing detailed characterization measurements on individual modules before assembly, the patent enables subsequent rapid quality assessment without requiring time-consuming comprehensive image tests on assembled detectors. This preliminary action maintains artifact detection precision while significantly improving production efficiency.
3Productivity
If qualitative analysis methods are used for detector evaluation, then assessment speed is improved, but measurement precision of image quality deteriorates
Solution Approach 1:
The patent creates a virtual model of the detector system using characterization data, enabling rapid quantitative analysis of image quality metrics. This virtual representation allows precise measurement of image quality parameters without requiring time-consuming physical image testing, thus resolving the contradiction between evaluation speed and measurement precision.
Solution Approach 2:
The patent transforms qualitative expert assessments into quantitative measurements by utilizing characterized parameters from individual detector modules. This parameter-based approach enables precise, objective image quality evaluation that can be performed rapidly using stored characterization data, improving both measurement precision and evaluation speed.
Data Source
AI summary
One or more example embodiments relates to a computer-implemented method for supporting the evaluation of characterization data of an X-ray detector for an X-ray imaging system, in particular for a computed tomography system, with a plurality of detector modules, wherein the method comprises the following steps: receiving characterization data for the detector modules of the X-ray detector, wherein at least part of the characterization data is based on measurement data of the detector modules recorded without an examination object; applying a trained algorithm to the characterization data, wherein the output generated is synthetic image data simulating image data of an X-ray imaging system, in particular a computed tomography system, recorded with the X-ray detector; providing the synthetic image data.