Ultrasound Decoding Filter Optimization for Axial Resolution
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Solution Overview
Problem
Current ultrasound decoding filters face challenges in achieving optimal echo signal-to-noise ratio (eSNR) due to limitations in pulse length and acoustic emission regulations, leading to suboptimal axial resolution and penetration depth, with existing methods requiring cumbersome and inaccurate factory-setting filter coefficients for each probe type.
Innovation Solution
A method for optimizing decoding filter coefficients through a heuristic iterative process, using real-time measurements and a reference nominal template to minimize differences between received and ideal signal characteristics, allowing for adaptive filter settings based on specific probe and medium characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pulse length is shortened to achieve short time response and improve axial resolution, then axial resolution is improved, but transmission energy and echo signal-to-noise ratio (eSNR) are reduced
Solution Approach 1:
The patent applies preliminary action by pre-coding the ultrasound pulse with a specific code sequence (e.g., Barker code, Golay code, or chirp signal) before transmission. This coded pulse contains embedded information that will be used later for compression and enhancement. The coding is performed in advance to enable subsequent signal processing that will extract maximum information content, thereby improving eSNR without requiring longer pulse lengths that would compromise axial resolution.
Solution Approach 2:
The patent changes the temporal structure parameters of the ultrasound signal by applying time-varying amplitude modulation through coding sequences. The pulse duration remains short for good axial resolution, but the signal is modulated with varying amplitude patterns (e.g., rise-time, plateau, fall-time structures) that encode additional information. This allows the system to maintain short pulse length while increasing the effective information content and improving eSNR through parameter modulation rather than extending pulse duration.
2Duration of action of stationary object
If coded transmission techniques are used to increase time-bandwidth product and improve penetration depth, then penetration depth is improved, but time sidelobes increase and axial resolution deteriorates
Solution Approach 1:
The patent implements feedback through the use of autocorrelation decoding filters that process the received coded signal. The filter uses feedback from the transmitted code sequence to generate a compressed echo signal. By comparing the received signal with the expected coded pattern and using this feedback information, the system can suppress time sidelobes and enhance the main peak, thereby maintaining axial resolution while achieving improved penetration depth through the increased time-bandwidth product.
Solution Approach 2:
The patent applies preliminary action by pre-designing the decoding filter characteristics based on the transmitted code sequence before signal reception. The filter is configured in advance with specific impulse response characteristics that are optimized for the chosen coding scheme. This preliminary configuration ensures that when the coded signal is received and processed, the system can immediately achieve optimal compression and sidelobe suppression without requiring adaptive adjustment, thereby maintaining axial resolution while enabling deeper penetration.
3Productivity
If matched filters are used for decoding to maximize signal compression, then signal compression is improved, but time sidelobes become unacceptable and image quality deteriorates
Solution Approach 1:
The patent changes the filter parameter by transitioning from a conventional matched filter to an optimized filter with modified impulse response characteristics. Instead of using a simple matched filter that maximizes compression but generates high sidelobes, the patent employs filters with specific parameter adjustments (e.g., windowing functions, apodization, or modified pulse shapes) that balance compression effectiveness with sidelobe suppression. This parameter optimization allows the system to achieve acceptable signal compression while keeping time sidelobes below unacceptable levels, thereby improving overall image quality.
Solution Approach 2:
The patent applies local quality by implementing different filter characteristics for different temporal regions of the signal. Instead of using a uniform filter that treats all parts of the pulse equally, the patent employs localized filtering strategies that apply different weighting or processing to different time segments of the coded signal. This allows the system to maximize compression of the main signal peak while simultaneously suppressing sidelobes in other temporal regions, achieving local optimization of both compression and sidelobe control.
4Ease of operation
If factory-setting filter coefficients are used for each probe type, then filter configuration is simplified, but the process becomes cumbersome and inaccurate
Solution Approach 1:
The patent implements self-service by enabling the ultrasound system to automatically determine and optimize filter coefficients based on actual system characteristics and measured performance. Instead of relying on pre-set factory values that may not accurately reflect specific probe or system variations, the system performs self-characterization by measuring the actual response of the probe and medium combination. This self-service approach allows the system to automatically adjust filter parameters to achieve optimal performance for each specific configuration, eliminating the need for manual factory-setting while improving accuracy.
Solution Approach 2:
The patent uses feedback mechanisms to continuously monitor and adjust filter coefficient accuracy based on actual signal processing performance. The system measures the output of the decoding process and compares it against expected characteristics, using this feedback information to refine and optimize the filter coefficients. This feedback loop enables the system to automatically correct inaccuracies in factory settings and adapt to variations in probe characteristics, medium properties, or operating conditions, thereby improving measurement precision without requiring complex manual configuration.
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 enhances the echo signal-to-noise ratio and reduces time sidelobes, improving axial resolution and penetration depth while simplifying the filter coefficient determination process, making it more efficient and accurate for various ultrasound applications.
Implementation Method 1
regulations-related requirements limit the characteristics of the acoustic emission
Implementation Method 2
the decoding filter actually is an autocorrelation filter, that is a device that operates in a nominal manner the signal convolution with its time-reversed copy
Data Source
AI summary
A method is provided for the optimization of the process decoding coded ultrasound signals that comprises: defining/selecting a coding function for ultrasound pulses transmitted to a body under examination by means of a predetermined probe; defining the coefficients of a filter decoding the received signal depending on the selected coding function; using said filter coefficients as the setting of the decoding filter corresponding to said predetermined probe for all the ultrasound systems provided in combination with said probe; and wherein the coefficients of the decoding filters are determined by the minimization, by a heuristic iterative process, of the difference between the characteristics of a receive signal, obtained in a real transmit/receive sequence and filtered with a decoding filter, and the characteristics of an ideal receive signal, that is a nominal one, by using as the coefficients of the decoding filter those obtained in the last iterative step.