Sparse Ultrasound Array Coarray Processing for Cavitation Monitoring
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Solution Overview
Problem
Current ultrasound imaging technologies for therapeutic ultrasound lack effective real-time monitoring strategies, particularly for high-intensity focused ultrasound (HIFU) ablation and ultrasound-enhanced drug delivery, as they fail to specifically monitor acoustic cavitation and harmonic emissions without the use of ultrasound contrast agents, and traditional 2-D arrays are costly and complex due to their large size and full element requirements.
Innovation Solution
A sparse 2-D array with a reduced number of elements is used, employing a processing system that calculates and applies weights to sensor data to generate images, utilizing a coarray concept to achieve high-resolution imaging similar to fully-filled arrays, and incorporating thin-film materials like PVDF for wideband detection and sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large 2-D aperture with fully-filled regularly-spaced array is used, then imaging resolution and 3-D spatial coverage are improved, but device complexity and manufacturing cost increase dramatically
Solution Approach 1:
The patent segments the fully-filled array into a sparse subset of elements while maintaining imaging capability through coarray processing. The sparse array is designed with specific geometric patterns that preserve the ability to form a complete coarray, enabling high-resolution imaging with fewer elements.
Solution Approach 2:
The patent transitions from direct spatial sampling in the physical array domain to sampling in the coarray domain through signal processing. By forming pseudo-elements through combinations of sparse array elements, the system achieves coverage equivalent to a dense array without the corresponding hardware complexity.
2Measurement precision
If a large 2-D aperture with fully-filled regularly-spaced array is used, then imaging resolution and 3-D spatial coverage are improved, but manufacturing cost increases dramatically
Solution Approach 1:
The patent reduces manufacturing cost by segmenting the array into only the necessary sparse elements required to form a complete coarray. This eliminates the need to manufacture and install numerous elements that would be present in a fully-filled array, while still achieving the same imaging resolution through coarray processing.
3Ease of manufacture
If traditional piezoceramic materials are used for array elements, then manufacturing is achieved, but cost and time consumption increase due to complex manufacturing processes
Solution Approach 1:
The patent changes the material parameter from traditional piezoceramics to thin-film materials, fundamentally altering the manufacturing approach. Thin-film fabrication techniques enable simpler, faster, and more cost-effective production compared to the complex processes required for piezoceramic element manufacturing.
4Device complexity
If a sparse array with fewer elements is used, then device complexity and cost are reduced, but imaging resolution and spatial coverage deteriorate
Solution Approach 1:
The patent introduces the coarray as an intermediary computational domain that bridges the sparse physical array and the desired dense imaging grid. Through coarray processing, the system synthesizes virtual elements that would exist in a dense array, thereby recovering the imaging resolution that would otherwise be lost due to sparsity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables cost-effective, high-resolution, real-time passive acoustic mapping of therapeutic ultrasound emissions, including cavitation monitoring, with improved sensitivity and reduced complexity, capable of providing 3-D spatial coverage and effective treatment monitoring.
Implementation Method 1
passive compression wave imaging system comprising an array of sensor elements arranged in an array, which may be a sparse array... The compression waves may be ultrasound waves
Implementation Method 2
incorporating thin-film materials like PVDF for wideband detection and sensitivity
Data Source
AI summary
A passive compression wave imaging system comprises an array of sensor elements arranged in a sparse array and a processor arranged to: store a plurality of samples of the output from each of the sensor elements over a sample period; derive from the stored samples a value for each of a set of image pixels; wherein for each of the image pixels the processing means is arranged to: define a plurality of different sets of weights for the elements of the sparse array; calculate a component of a pixel value from each of the sets of weights and the stored samples; and sum the components of the pixel value to produce a final pixel value.