Volume-Based Image Registration for Ultrasound Alignment
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Solution Overview
Problem
The challenge in medical imaging is the laborious and time-consuming process of registering ultrasound images with pre-acquired image volumes due to patient movement, which leads to misalignment, especially when using different imaging modalities.
Innovation Solution
A method and system for volume-based registration of images that involves receiving multiple image datasets, identifying corresponding points of interest, and translating them in three directions to align, thereby updating the registration and generating a registered image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual registration methods are used to align ultrasound images with pre-acquired volume data sets, then registration accuracy can be achieved, but the process becomes laborious and time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically identifying corresponding points between the ultrasound image and pre-acquired volume data set before final registration. This includes detecting anatomical landmarks and establishing initial alignment, which reduces the manual workload and time required for the operator to complete the registration process while maintaining accuracy
2Speed
If position sensing systems with sensors mounted on ultrasound transducers are used, then real-time tracking is achieved, but the registration process remains complex and time-consuming
Solution Approach 1:
The system extracts and utilizes position information from the position sensing system without requiring complex sensor mounting on the ultrasound transducer. By separating the position tracking function from the imaging function and integrating it into the registration workflow, the system simplifies the overall process while maintaining real-time tracking capability
Solution Approach 2:
The registration system is designed to work with multiple imaging modalities (ultrasound, CT, MR, PET) and position sensing approaches, making it a universal solution that handles different scenarios without requiring modality-specific complex procedures. This multi-functionality reduces operational complexity across various clinical applications
3Loss of information
If multiple imaging modalities are used for scanning, then comprehensive diagnostic information is obtained, but patient position varies leading to inherent registration problems
Solution Approach 1:
The system adapts to different imaging modalities by adjusting registration parameters and algorithms specific to each modality's characteristics (e.g., resolution, contrast, anatomical coverage). This allows comprehensive use of multiple modalities while compensating for position variations through modality-optimized registration techniques
Solution Approach 2:
The system introduces an intermediary reference coordinate system that mediates between different imaging modalities. By transforming all images into this common reference frame using identified corresponding points and anatomical landmarks, the system reconciles position variations across modalities while preserving the diagnostic information from each
Data Source
AI summary
A method for volume based registration of images is presented. The method includes receiving a first image data set and at least one other image data set. Further the method includes identifying a first image slice in the at least one other image data set corresponding to the first image data set. The method also includes selecting a first point of interest on at least one of the first image data set or the first image slice in the at least one other image data set. In addition, the method includes selecting a second point of interest on the other of the first image data set or the first image slice in the at least one other image data set, wherein the second point of interest corresponds to the first point of interest. Moreover, the method includes translating one of the first image data set, the first image slice, or both, in a first direction, a second direction and a third direction to align the first point of interest with the second point of interest. Also, the method includes registering the first image data set and the at least one other image data set. Systems and computer-readable medium that afford functionality of the type defined by this method is also contemplated in conjunction with the present technique.