Medical Imaging Stitching Verification
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Solution Overview
Problem
Medical imaging systems face challenges in precisely stitching images from multiple regions scanned with different parameters, leading to errors and inefficiencies in generating a comprehensive image of a subject.
Innovation Solution
A system and method that determine and adjust scanning and stitching parameters for each region, generating image stitching verification data to ensure consistency and accuracy, allowing for optimal scanning and image reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If images of multiple regions are stitched using different scanning parameters, then the field of view is expanded to cover the entire subject, but stitching errors occur reducing image quality and accuracy
Solution Approach 1:
The system performs preliminary determination of stitching parameters between protocols corresponding to neighboring regions before the actual scanning process. Image stitching verification data is generated in advance based on these parameters, allowing the system to verify stitching feasibility before committing to the scan, thereby preventing stitching errors while maintaining expanded field of view capability
Solution Approach 2:
The system generates image stitching verification data that provides feedback on whether the determined stitching parameters will produce accurate results. This verification mechanism allows the system to identify and correct potential stitching issues before they affect the final image quality, resolving the contradiction between expanded coverage and stitching precision
2Area of stationary object
If multiple scanning sessions are performed for different regions, then complete coverage of the subject is achieved, but the imaging time increases due to repetitive scans
Solution Approach 1:
The system determines stitching parameters and generates verification data before scanning begins. This preliminary verification prevents stitching errors that would otherwise require repetitive scanning sessions, thereby reducing total imaging time while maintaining complete subject coverage
Solution Approach 2:
By verifying stitching parameters in advance, the system can proceed directly through the scanning process without interruptions for corrective re-scans. The verification data allows the system to skip unnecessary repetitive scanning sessions that would otherwise be required to correct stitching errors
3Adaptability or versatility
If stitching parameters are determined after scanning, then flexibility in parameter adjustment is maintained, but errors occur reducing the success rate of image stitching
Solution Approach 1:
The system determines and verifies stitching parameters before the scanning process begins. This preliminary determination maintains flexibility in parameter selection while simultaneously improving reliability by identifying and correcting potential stitching issues before they can affect the final result
Solution Approach 2:
The system performs self-verification of stitching parameters by generating image stitching verification data that automatically checks whether the determined parameters will produce accurate stitching results. This self-service mechanism ensures both flexibility in parameter choice and high reliability in stitching outcomes
Data Source
AI summary
The present disclosure provides a system and method for imaging. The method may include obtaining a plurality of protocols for scanning a subject using a scanner, wherein the plurality of protocols correspond to a plurality of regions of the subject, respectively. The method may also include determining one or more stitching parameters between protocols corresponding to each pair of neighboring regions of the plurality of regions. The method may further include generating image stitching verification data associated with the plurality of regions based at least in part on at least one of the one or more stitching parameters between protocols corresponding to each pair of neighboring regions of the plurality of regions. The method may still further include directing the scanner to scan the subject based at least in part on the image stitching verification data.