Ultrasound Frequency Selection via Spatial Coherence
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Solution Overview
Problem
Current ultrasound imaging methods lack real-time adaptive frequency selection, leading to acoustic clutter that reduces image quality and obscures target details due to reverberation, phase aberration, and off-axis scattering.
Innovation Solution
An ultrasound system employing a transducer and control system with a bandpass filter and processor to calculate spatial coherence of pulse-echo data, predicting target conspicuity and selecting a preferred frequency to mitigate clutter and enhance image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional ultrasound imaging methods are used, then the system structure remains simple and operation is straightforward, but acoustic clutter from reverberation, phase aberration, and off-axis scattering reduces image quality and obscures target details
Solution Approach 1:
The system performs preliminary coherence analysis and frequency selection before acquiring the final clinical images. Pilot pulses are transmitted over a range of frequencies, coherence is calculated for each frequency, and the optimal frequency is selected in advance to minimize clutter in the subsequent imaging process
Solution Approach 2:
The system calculates coherence metrics from received echo data and uses this feedback to adaptively select the optimal transmit frequency. The coherence calculation provides feedback about which frequencies produce the least clutter, allowing the system to adjust frequency selection based on real-time tissue characteristics
2Object-affected harmful factors
If frequency sweep with pilot pulses is performed to calculate coherence and select optimal frequency, then image quality improves by reducing clutter, but imaging time increases due to the additional frequency sampling process
Solution Approach 1:
The system transmits pilot pulses over a range of frequencies that extends beyond the final selected frequency. This partial frequency sweep allows coherence to be calculated at multiple frequencies to identify the optimal one, while the excessive frequency range ensures the true optimal frequency is captured even if not precisely predicted
Solution Approach 2:
The coherence calculation and frequency selection are performed as a preliminary step before acquiring the full clinical image set. By selecting the optimal frequency in advance using a rapid coherence metric calculation, the system avoids the need to perform time-consuming post-processing or acquire multiple complete image sets at different frequencies
3Adaptability or versatility
If a fixed frequency is used for ultrasound imaging, then the system operation is simple and fast, but image quality varies across different tissue types and patients due to inability to adapt to different acoustic environments
Solution Approach 1:
The system dynamically adjusts the transmit frequency based on calculated coherence metrics from the specific patient's tissue. Rather than using a static fixed frequency, the system adapts the frequency selection to match the acoustic properties of the individual patient's tissue, optimizing image quality for each unique acoustic environment
Solution Approach 2:
The system automatically performs coherence analysis and frequency selection without requiring operator intervention. The ultrasound system itself evaluates the coherence at different frequencies and autonomously selects the optimal frequency for imaging, eliminating the need for manual frequency adjustment by the operator
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
The system achieves improved ultrasound image quality by selecting a frequency that balances image contrast, resolution, and target size, effectively suppressing clutter and enhancing visibility of imaging targets.
Implementation Method 1
An acoustic wave can be emitted from an array of piezoelectric elements, propagated through tissue in a selected acoustic window, and reflected back to the array elements
Implementation Method 2
An acoustic wave can be emitted from an array of piezoelectric elements, propagated through tissue in a selected acoustic window, and reflected back to the array elements
Implementation Method 3
the signal of the pulse-echo data is bandpass-filtered through a bandpass filter within the control system. The signal is bandpass-filtered over a variety of frequency ranges which either match a transmit frequency or span a bandwidth of excitation
Implementation Method 4
An acoustic wave can be emitted from an array of piezoelectric elements, propagated through tissue in a selected acoustic window, and reflected back to the array elements
Data Source
AI summary
An ultrasound system is disclosed. Embodiments in accordance with the present invention include a transducer configured to acquire pulse-echo data at each transmit frequency bandwidth of interest. In addition, a bandpass filter is configured to receive a signal of the pulse-echo data, wherein the signal is bandpass-filtered over a plurality of frequencies. Further, a processor is configured to calculate a spatial coherence of the bandpass-filtered signal. The spatial coherence of the signal is calculated in a spatial domain or a frequency domain. The spatial coherence is used to predict target conspicuity. The processor selects a preferred frequency based on and, preferably, to realize, the target conspicuity.