Adaptive Frame Averaging in Ultrasound Systems
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Solution Overview
Problem
Conventional ultrasound systems perform frame averaging based on a fixed coefficient, leading to motion blurring when the frame rate changes, especially when the body or target object moves, as they fail to adaptively adjust the frame average process to changing frame rates.
Innovation Solution
An adaptive frame average process is implemented in the ultrasound system, where a coefficient estimating section determines frame rate changes and adjusts the frame average coefficients accordingly, allowing the system to dynamically resample and interpolate ultrasound images to maintain image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed frame average coefficient is used in the frame average process, then the signal-to-noise ratio is improved, but motion blurring occurs when the frame rate changes or the living body moves
Solution Approach 1:
The patent applies the Dynamics principle by making the frame average coefficient adaptive rather than fixed. The coefficient estimating section dynamically adjusts the frame average coefficient based on the detected frame rate change, allowing the system to maintain optimal image quality under varying conditions. This resolves the contradiction by enabling the system to switch between high averaging (for noise reduction) and low averaging (for motion clarity) based on real-time operational parameters.
Solution Approach 2:
The patent implements Parameter changes by modifying the frame average coefficient in response to frame rate changes. When the frame rate changes, the coefficient estimating section detects this change and adjusts the frame average coefficient accordingly. This dynamic parameter adjustment allows the system to maintain measurement precision (signal-to-noise ratio) while avoiding motion blurring that occurs with fixed coefficients.
2Measurement precision
If the frame average coefficient is increased to improve image quality, then the signal-to-noise ratio improves, but the responsiveness of the ultrasound image degrades
Solution Approach 1:
The system dynamically adjusts the frame average coefficient based on frame rate changes, allowing it to optimize between image quality and responsiveness in real-time. When frame rates are stable and high, higher averaging can be applied for better quality. When frame rates change or are low, the coefficient is reduced to maintain responsiveness, thus resolving the contradiction between these two competing requirements.
Solution Approach 2:
By changing the frame average coefficient parameter in response to frame rate conditions, the system can adaptively balance image quality and responsiveness. The coefficient estimating section monitors frame rate changes and adjusts the averaging parameter accordingly, enabling the system to achieve high image quality when conditions permit while maintaining responsiveness when frame rates are limited or changing.
3Object-affected harmful factors
If adaptive frame average process is implemented to reduce motion blurring, then image quality during movement is improved, but device complexity increases
Solution Approach 1:
The patent implements feedback by having the coefficient estimating section detect frame rate changes and use this information to adjust the frame average coefficient. This closed-loop feedback mechanism allows the system to automatically adapt to changing conditions and reduce motion blurring without requiring complex manual intervention or overly sophisticated algorithms, thus managing device complexity while improving image quality during movement.
Solution Approach 2:
The system performs self-service by automatically detecting frame rate changes and adjusting its own frame average coefficient without external intervention. The coefficient estimating section monitors system operation and autonomously modifies the averaging parameter to optimize image quality, reducing the need for complex external control mechanisms while effectively combating motion blurring.
Data Source
AI summary
There are provided embodiments for performing a frame average process based on a change of a frame rate are disclosed. In one embodiment, an ultrasound system comprises: an ultrasound data acquisition unit configured to sequentially acquire ultrasound data corresponding to a living body; and a processing unit configured to sequentially form a plurality of ultrasound images based on the ultrasound data, estimate a frame average coefficient corresponding to a change of a frame rate based on an i th (i is a positive integer) ultrasound image and an i th frame average image, and perform a frame average process between the i th frame average image and an (i+1) th ultrasound image based on the frame average coefficient to form an (i+1) th frame average image.