Dark Field Lung Imaging Differentiation for Air-Soft Tissue Interface Detection
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Solution Overview
Problem
Absorption computed tomography imaging systems struggle to effectively detect air-soft tissue interfaces in the lung, limiting their usability in assessing lung health.
Innovation Solution
A system that generates and processes dark field images of the lung, differentiating them based on breathing states to enhance the detection of air-soft tissue interfaces, using a dark field image providing unit and an image processing unit that applies motion correction algorithms to improve image quality and sensitivity for lung disease detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If absorption computed tomography imaging is used to image the lung, then the imaging system can provide structural information, but air-soft tissue interfaces are not well detectable
Solution Approach 1:
The imaging system segments the measurement into two distinct components: absorption imaging for structural information and dark field imaging for microstructural interface detection. This segmentation allows each modality to optimize for its specific strength, with dark field imaging specifically targeting air-soft tissue interfaces while absorption imaging provides overall lung structure.
Solution Approach 2:
The system combines two different imaging modalities (absorption computed tomography and dark field imaging) into a composite imaging approach. This composite method integrates the structural information from absorption imaging with the high sensitivity to air-soft tissue interfaces from dark field imaging, creating a more comprehensive assessment tool.
2Measurement precision
If dark field imaging is used to detect air-soft tissue interfaces, then detection sensitivity is improved, but the system complexity increases
Solution Approach 1:
The system merges the dark field imaging capability with the existing absorption computed tomography system. By combining these modalities in a single integrated system that rotates around the subject, the patent achieves high detection sensitivity for air-soft tissue interfaces while managing system complexity through unified hardware architecture.
Solution Approach 2:
The imaging system is designed with multi-functionality, serving both absorption imaging and dark field imaging purposes. The same rotating framework and detector system perform both types of measurements, making the complex dark field capability accessible through a universal platform rather than requiring separate dedicated equipment.
3Measurement precision
If differentiation with respect to breathing state values is applied, then functional information and sensitivity to changes are enhanced, but processing complexity increases
Solution Approach 1:
The system performs preliminary organization of dark field values according to breathing state values before differentiation. By pre-sorting and structuring the data during acquisition, the subsequent differentiation process becomes more straightforward and manageable, reducing processing complexity while maintaining high sensitivity to functional changes.
Solution Approach 2:
The differentiation process creates feedback between the breathing state information and the image processing. By using breathing state values as a reference framework, the system continuously refines its detection of changes, where the known breathing patterns provide feedback that guides the differentiation algorithm to focus on relevant physiological variations.
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
The system provides a functional image with high sensitivity for detecting changes in air-soft tissue interfaces, enabling improved assessment of lung health by integrating dark field values over breathing states and spatial positions, effectively addressing the limitations of traditional absorption computed tomography imaging.
Implementation Method 1
an x-ray source and an x-ray detector, which are rotatable around a subject's lung to be imaged such that x-rays generated by the x-ray source traverse the lung in different directions. The x-ray detector detects the x-rays after having traversed the lung
Implementation Method 2
a dark field image providing unit for providing a dark field image of the lung, wherein the provided dark field image comprises dark field values for different spatial positions and for different breathing state values
Data Source
AI summary
The invention relates to a system (1) for assisting in assessing a state of a subject's lung. The system is adapted to process a dark field image, which comprises dark field values for different spatial positions and for different breathing state values, such that a differentiation image is generated by differentiating the provided dark field image with respect to the breathing state values. This differentiation can lead to a functional image which can be used for detecting changes of air-soft tissue interfaces, which might be caused by a lung disease, with high sensitivity. This allows for an improved assisting in assessing a state of a subject's lung.