Microbubble Tracking for Super-Resolution Microvessel Ultrasound
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ultrasound imaging methods struggle to achieve super-resolution imaging of microvessels due to the diffraction limit and are susceptible to noise and tissue motion, which affects microbubble tracking and accumulation.
Innovation Solution
A method for super-resolution imaging of microvessels using ultrasound data processing to isolate, localize, and globally track microbubbles, employing techniques such as bipartite graph minimal distance pairing and spatiotemporal denoising to produce high-resolution microvessel images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ultrasound imaging methods are used, then imaging is straightforward, but resolution is limited by the diffraction limit and cannot resolve microvessels smaller than half the ultrasound wavelength
Solution Approach 1:
The patent segments the imaging process into distinct stages: microbubble isolation, localization, tracking, and accumulation. By dividing the complex super-resolution imaging task into manageable segments, the method achieves enhanced spatial resolution while maintaining systematic control over the increased complexity
Solution Approach 2:
The patent transitions from conventional 2D spatial imaging to 4D imaging by adding the temporal dimension through high frame-rate acquisition. This dimensional expansion enables super-resolution capability by tracking microbubble motion over time, allowing resolution beyond the diffraction limit while managing complexity through temporal processing
2Reliability
If microbubble tracking and accumulation techniques are used to achieve super-resolution imaging, then hemodynamics measurements can be obtained, but the methods are susceptible to noise and tissue motion
Solution Approach 1:
The patent applies preliminary denoising processing to ultrasound data before microbubble tracking and accumulation. By removing noise and tissue motion artifacts in advance, the tracking accuracy is significantly improved, and the reliability of hemodynamics measurements is enhanced while mitigating the harmful effects of noise and motion
Solution Approach 2:
The patent implements feedback mechanisms through iterative tracking and accumulation processes that continuously refine microbubble position estimates. This feedback approach improves tracking reliability by correcting errors and compensating for residual noise and tissue motion effects throughout the imaging sequence
3Measurement precision
If high frame-rate ultrasound is used to monitor microbubble blinking events, then isolated microbubble signals can be obtained, but data processing complexity increases
Solution Approach 1:
The patent segments the high frame-rate data processing into distinct operational phases: microbubble detection, blinking event identification, and signal isolation. This segmentation reduces processing complexity by handling each aspect separately rather than processing all data simultaneously, while maintaining precise microbubble signal isolation
Solution Approach 2:
The patent extracts and isolates microbubble signals from the high frame-rate ultrasound data by identifying characteristic blinking patterns. This extraction approach achieves precise microbubble signal isolation while reducing processing complexity by focusing computational resources only on relevant microbubble events rather than processing all tissue signals
Data Source
Figure 1
Figure 2~3
Figure 4~6
AI summary
A method for super-resolution imaging of microvessels using an ultrasound system is provided. Ultrasound data, which has been acquired with an ultrasound system from a region-of-interest in a subject, is provided to a computer system. A microbubble contrast agent was present in the subject when the ultrasound data were acquired. Microbubble signal data is generated with the computer system by isolating microbubble signals in the ultrasound data from other signals in the ultrasound data. Microbubbles are localized in the microbubble signal data by processing the microbubble signal data with the computer system to determine spatial locations associated with microbubbles in the microbubble signal data. A super-resolution microvessel image is produced based at least in part on the localized microbubble signals, wherein the microbubbles are globally tracked as a function of time and the microvessel image is produced based on that tracking of the microbubbles.