Dynamic Reference Imaging Data Update for Ultrasound Fusion
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Solution Overview
Problem
Fusing current 2D and 3D ultrasound imaging data with previously acquired reference data is a time-intensive task and often results in visual clutter and misalignment issues during medical procedures.
Innovation Solution
A computing system that dynamically updates reference imaging data by registering and comparing previously acquired data with newly acquired update data, adding or subtracting structural and functional information to reflect changes, thereby providing a current snapshot for clinicians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If 2D and 3D imaging data is fused with reference imaging data, then the information completeness is improved, but the processing time increases significantly
Solution Approach 1:
The system performs registration of update imaging data with reference imaging data in advance, before the actual surgical procedure begins. This preliminary registration allows the system to pre-process and align multiple imaging datasets, so that during the procedure, only minimal real-time updates are needed rather than complete re-processing of all data
Solution Approach 2:
The system dynamically updates the reference imaging data with newly acquired update imaging data during the procedure. Instead of static fusion performed once, the system continuously registers and integrates new imaging data as it becomes available, adapting the reference dataset in real-time to reflect current anatomical conditions
2Loss of information
If multiple imaging data sets are overlaid during the procedure, then the information availability is improved, but visual clarity deteriorates due to clutter and misalignment
Solution Approach 1:
The system merges update imaging data with reference imaging data into a single integrated dataset through registration. Instead of displaying multiple separate overlaid datasets that create visual clutter, the registered data is combined into one coherent reference dataset that maintains alignment and reduces visual complexity
Solution Approach 2:
The system applies different processing and display characteristics to different regions of the imaging data. Registered and updated regions are integrated seamlessly with the reference data, while unregistered regions maintain their original characteristics. This allows selective integration of high-quality registered data in critical areas while preserving original data elsewhere
Data Source
AI summary
A method includes obtaining reference imaging data. The reference imaging data is acquired at a first time and includes tissue of interest. The method further includes obtaining update imaging data. The update imaging data is acquired at a second time. The second time is subsequent to the first time. The method further includes identifying a difference between the reference imaging data and the update imaging data. The method further includes changing the reference imaging data based on the identified difference. The method further includes displaying the changed reference imaging data.


