Energy-Resolving X-Ray Detector Mixing Spatial Resolution
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Solution Overview
Problem
Existing X-ray detectors face challenges in adjusting spatial resolution after data recording, particularly in clinical applications where finer details like stents need to be identified, due to limitations in detector element size and energy threshold settings, which affect image quality and frame rates.
Innovation Solution
A method and image-generating unit that allow for the mixing of image data records from different energy ranges based on image parameters, enabling retrospective adjustment of spatial resolution by generating and mixing first and second image values in specific energy ranges and applying filtering and optimization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If smaller detector elements are used to increase spatial resolution, then spatial resolution is improved, but pixel noise increases and frame rates decrease
Solution Approach 1:
The detector matrix is divided into multiple detector elements with different sizes. Larger detector elements are used to maintain high frame rates and reduce pixel noise, while smaller detector elements provide high spatial resolution. The system segments the detector into different functional regions that can be independently utilized based on clinical requirements.
Solution Approach 2:
Different regions of the detector are assigned different detector element sizes optimized for different purposes. Certain regions use smaller elements for high spatial resolution requirements, while other regions use larger elements for high frame rate requirements. This local optimization allows the system to simultaneously achieve both high spatial resolution and high frame rates in different areas.
2Measurement precision
If smaller detector elements are used to increase spatial resolution, then spatial resolution is improved, but pixel noise increases
Solution Approach 1:
The detector is segmented into multiple elements with varying sizes. Larger detector elements inherently produce less pixel noise due to their greater light-collecting area, while smaller elements provide higher spatial resolution where needed. This segmentation allows the system to manage pixel noise by utilizing larger elements in regions where noise is a concern.
Solution Approach 2:
Different detector element sizes are distributed across the detector matrix to optimize local performance. Regions requiring low noise use larger detector elements, while regions requiring high spatial resolution use smaller elements. This local quality variation allows simultaneous optimization of both spatial resolution and noise characteristics across different areas of the detector.
3Device complexity
If energy threshold values are set globally for the entire X-ray detector, then device complexity is reduced, but adaptability to different clinical applications decreases
Solution Approach 1:
The energy threshold configuration is segmented from a single global setting into multiple region-specific or element-specific thresholds. This allows different energy ranges to be optimized for different clinical applications (e.g., bone imaging, soft tissue imaging, contrast agent detection) without increasing overall system complexity, as each region can be independently configured based on its specific requirements.
Solution Approach 2:
The energy threshold values are made dynamically adjustable for different detector elements or regions, allowing the system to adapt to various clinical applications in real-time. This dynamic configuration capability enables the detector to optimize its performance for different imaging tasks without requiring physical reconfiguration, thereby increasing adaptability while maintaining manageable system complexity through software control.
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 approach enhances spatial resolution and improves image quality by selectively increasing the weighting of higher energy range information in regions with high signal or low movement, thereby improving diagnostic clarity without compromising signal-to-noise ratios.
Implementation Method 1
In direct-conversion X-ray detectors, the X-rays or photons can be converted into electrical pulses by way of a suitable converter material
Data Source
AI summary
A method is for generating a mixed image data record based on energy-resolved recording via an energy-resolving X-ray detector. In an embodiment, the method includes generating a first image value of a first image element of a first image data record in a first energy range and generating a second image value of the first image element of a second image data record in a second energy range; and mixing the first image value generated and the second image value generated in dependence on an image parameter, to generate the mixed image data record with a mixed image value of the first image element.