Spectral Image Registration for Coronary Segments
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Solution Overview
Problem
Establishing a spatial correspondence between segments or slices of coronaries in spectral image data sets acquired at different time points is challenging due to the complexity introduced by dual energy mode CCTA images and the large number of spectral result images.
Innovation Solution
A device and method for image processing that involves obtaining two spectral image data sets, performing a first alignment using image registration, identifying corresponding coronary segments, and then performing a finer alignment using multi-channel image registration to determine image differences between the aligned data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image registration is applied directly on 3D CCTA image volumes, then large structures (heart and lungs) can be aligned, but smaller coronary trees receive less alignment focus and spatial correspondence is insufficient
Solution Approach 1:
The patent segments the spectral image data processing into distinct stages: first performing image registration on the complete 3D CCTA volumes to achieve coarse alignment of large structures, then identifying and extracting coronary segments, and finally performing a second registration specifically on these segmented coronary regions to achieve fine alignment. This segmentation allows each registration stage to focus on appropriate anatomical structures, improving overall alignment precision without overwhelming complexity at each step
Solution Approach 2:
The patent extracts coronary segments from the larger 3D CCTA volume after initial alignment. By taking out the coronary trees as separate segmented structures, the system can apply specialized multi-channel image registration techniques focused specifically on these smaller vessels, achieving higher alignment precision for coronary segments that would be lost in a whole-volume registration approach
2Loss of information
If multiple spectral CT images are acquired in dual energy mode, then comprehensive spectral information is obtained, but the complexity of establishing correspondence increases due to large number of image pairs and spectral result images
Solution Approach 1:
The patent performs preliminary image registration on the spectral image data sets before conducting detailed spectral analysis or comparison. By establishing the spatial correspondence and alignment framework in advance, the system creates a structured foundation that simplifies subsequent spectral image processing, allowing comprehensive spectral information to be analyzed without being overwhelmed by the complexity of establishing correspondences across multiple spectral channels and time points
Solution Approach 2:
The patent applies different processing strategies to different spectral channels and image types based on their specific characteristics. Rather than treating all spectral images uniformly, the system adapts the registration and analysis approach to the local quality and properties of each spectral channel, optimizing the balance between information completeness and processing complexity for each specific image type
Data Source
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AI summary
The present invention relates to a device and method for image processing of spectral images of a subject. The device comprises an input unit configured to obtain two spectral image data sets of a region of interest, ROI, of the subject acquired at different points in time, each spectral image data set comprising two or more spectral images of the ROI in two or more different channels, the ROI including coronaries. A processing unit is configured to perform a first alignment of the two spectral image data sets by use of image registration; identify one or more corresponding coronary segments in the aligned spectral image data sets; perform a second alignment of the two spectral image data sets, which is a finer alignment than the first alignment, by use of multi-channel image registration of the one or more corresponding coronary segments; and determine, per channel, image differences between the finer aligned spectral image data sets. An output unit is provided to output the finer aligned spectral images of the channel having the largest image differences.