Functional Image Morphing for Motion-Induced PET-CT Mismatch
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Solution Overview
Problem
Existing multi-modality medical imaging techniques fail to accurately match functional image data with anatomical image data due to spatial mismatch caused by respiratory, cardiac, or sporadic patient motion, leading to unreliable functional-anatomical structural correlation and compromised image quality.
Innovation Solution
A system and method for spatial mismatch correction that identifies voxels of reconstruction inconsistency between true and derived attenuation values, allowing functional image data to be morphed independently of structural correlation, maintaining image quality through localized morphing based on anatomical image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing PET reconstruction or image registration techniques are used to spatially match functional and anatomical image data, then functional-anatomical structural correlation is achieved, but image quality deteriorates due to unreliable correlation from motion-induced spatial mismatch
Solution Approach 1:
The patent segments the functional image data into multiple subsets corresponding to different respiratory phases or motion states. Each subset is independently registered with the anatomical image data, allowing for more accurate alignment without compromising overall image quality. This segmentation approach resolves the contradiction by enabling reliable structural correlation while maintaining diagnostic image quality through phase-specific registration.
Solution Approach 2:
The patent transforms the functional image data from a single static representation into multiple dynamic representations parameterized by respiratory phase or motion state. By changing the parameterization of the functional data, the system achieves reliable structural correlation across different physiological states while preserving the original image quality characteristics through parameter-driven transformation rather than direct spatial registration.
2Measurement precision
If functional image data is spatially matched with anatomical image data using traditional registration techniques, then attenuation correction is improved, but original image quality is lost due to morphing operations
Solution Approach 1:
The patent introduces an intermediary attenuation map derived from the anatomical image data that is used to correct the functional image data without directly morphing the original functional data. This intermediary attenuation correction mechanism improves measurement precision for attenuation correction while preserving the original image quality by avoiding direct spatial transformation of the diagnostic functional image data.
Solution Approach 2:
The patent creates a copy of the functional image data that is used for registration and attenuation correction purposes, while the original functional image data remains unchanged for diagnostic interpretation. This copying approach allows accurate attenuation correction to be applied based on registered anatomical data while the original image quality is preserved in the unmodified functional data copy.
3Reliability
If rigid registration is applied to align functional and anatomical image data, then spatial matching is achieved, but reconstruction inconsistency artifacts increase due to motion during acquisition
Solution Approach 1:
The patent transitions from static rigid registration to dynamic registration that accounts for respiratory motion and other physiological movements during data acquisition. By making the registration process dynamic and adaptive to motion states, the system achieves accurate spatial matching while minimizing reconstruction inconsistency artifacts that arise from attempting to align data acquired during different phases of motion.
Solution Approach 2:
The patent performs preliminary sorting or gating of the functional image data into motion phases before registration is applied. This preliminary action of organizing data by motion state prevents reconstruction inconsistency artifacts by ensuring that data from similar physiological states are registered together, thereby achieving reliable spatial matching without the artifacts that would result from mixing motion-phase data.
Data Source
AI summary
A system includes a spatial mismatch correction module configured to receive functional emission data, anatomical image data, and functional image data reconstructed based on the functional emission data and attenuation corrected based on the anatomical image data. The system further includes a data set provider configured to provide a first data set and a second data set, which are spatially mismatched. The system further includes a voxel of interest identifier configured to identify voxels or regions of reconstruction inconsistency due to a spatial mismatch between true attenuation values and attenuation values derived from the anatomical image data based on relations between the first and second data sets. The system further includes an image data generator configured to morph the functional image data and generate corrected functional image data based on the identified voxels or regions, independent of functional-anatomical structural correlation, while maintaining an image quality of the functional image data.