Ultrasound Imaging System Depth Derivation and Parameter Optimization
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Solution Overview
Problem
Ultrasonic diagnostic imaging systems require frequent adjustments of various settings to achieve optimal imaging conditions, which can be challenging for users, especially inexperienced ones, due to indirect feedback mechanisms and the need for iterative adjustments.
Innovation Solution
An ultrasound imaging system with a user interface that allows users to select a point or region of interest on the image, enabling automated or semi-automated adjustment of imaging parameters such as frequency, frame rate, and focal zone to optimize imaging for specific anatomical features, using techniques like model-based segmentation and closed-loop control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated parameter adjustment is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system automatically adjusts imaging parameters by detecting anatomical features and depth information from the ultrasound image, eliminating the need for manual parameter tuning by the operator. The processing system autonomously controls transmission frequency, frame rate, and focal zone based on image content analysis.
Solution Approach 2:
The system uses feedback from image quality metrics and detected anatomical features to continuously optimize imaging parameters. The processing system analyzes the ultrasound image, identifies regions of interest, and adjusts parameters based on this feedback loop to maintain optimal image quality.
2Adaptability or versatility
If multiple controls are provided for parameter adjustment, then adaptability is improved, but device complexity increases
Solution Approach 1:
A single user interface element (the ultrasound image itself) serves multiple functions: it displays image data, allows region selection, provides depth information, and triggers parameter adjustment. This multi-functional approach eliminates the need for separate controls for each parameter type.
Solution Approach 2:
The system combines multiple parameter adjustment functions (frequency, frame rate, focal zone) into a single automated process triggered by image analysis. Instead of separate controls for each parameter, the system merges them into one unified adaptive control mechanism.
3Measurement precision
If iterative adjustment process is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary analysis of the ultrasound image to detect anatomical features and estimate optimal parameters before final image acquisition. This preliminary action prevents the need for multiple iterative adjustments by pre-configuring appropriate parameters based on initial image content analysis.
Solution Approach 2:
The system replaces the manual iterative adjustment process with automated image analysis and parameter optimization using computer vision algorithms and machine learning models. This substitution eliminates the time-consuming back-and-forth manual tuning while maintaining or improving parameter precision.
Data Source
AI summary
An ultrasound imaging system comprises a display for displaying a received ultrasound image. A user interface is provided for receiving user commands for controlling the ultrasound imaging process, and it receives a user input which identifies a point or region of the displayed ultrasound image. An image depth is determined which is associated with the identified point or region and the imaging process is controlled to tailor the imaging to the identified point or region.