Ultrasound Diagnostic Device Adaptive Imaging Condition Adjustment
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Solution Overview
Problem
Current ultrasound diagnostic apparatuses face challenges in finely identifying diagnostic parts, especially in emergency situations like eFAST testing, where general imaging conditions are used for multiple parts, leading to insufficient information for precise identification and difficulty in selecting appropriate imaging conditions for unknown parts.
Innovation Solution
The ultrasound diagnostic apparatus incorporates an image analyzing unit, a part probability calculating unit, and an imaging condition changing unit to analyze ultrasound images, calculate probabilities based on orientation angles and image analysis results, and adjust imaging conditions to enhance part identification, even when initial conditions are inadequate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If general imaging conditions are used for multiple diagnostic parts, then the imaging process can be simplified and operated quickly, but the amount of information for identifying each diagnostic part becomes insufficient and fine identification becomes difficult
Solution Approach 1:
The system automatically adjusts imaging conditions based on feedback from image analysis results and probability calculations. The image analyzing unit analyzes captured images, the part probability calculating unit calculates probabilities of different parts based on orientation angles and image features, and the imaging condition changing unit automatically adjusts imaging conditions based on these calculations, creating a closed-loop feedback system that improves identification accuracy without sacrificing imaging speed
Solution Approach 2:
The ultrasound diagnostic apparatus performs self-adjustment of imaging conditions through automated image analysis and probability calculation. The system serves itself by automatically analyzing captured images, determining which part is being imaged through probability calculations, and adjusting imaging conditions without requiring manual intervention from the operator, thereby maintaining high imaging speed while improving identification accuracy
2Measurement precision
If manual setting of imaging conditions is performed for each diagnostic part, then appropriate imaging conditions can be obtained, but the operator needs to set imaging conditions every time the part to be captured changes, increasing operation time
Solution Approach 1:
The system automatically performs the task of selecting and setting appropriate imaging conditions by itself. The image analyzing unit analyzes the captured image, the part probability calculating unit determines which part is being imaged, and the imaging condition changing unit automatically selects and applies the appropriate imaging conditions from stored conditions, eliminating the need for manual operator intervention and significantly reducing condition setting time
Solution Approach 2:
The system performs preliminary analysis of captured images and calculates part probabilities before final imaging condition selection. By pre-storing multiple imaging conditions associated with different parts and pre-analyzing image features, the system prepares everything in advance so that when imaging is needed, the appropriate conditions can be quickly selected and applied without manual intervention
3Measurement precision
If pattern recognition databases with extensive information are used, then diagnostic part identification accuracy can be improved, but data processing and analysis time increases
Solution Approach 1:
Instead of using extensive comprehensive databases, the system focuses on calculating probabilities for specific parts based on local image features and orientation angles. The part probability calculating unit calculates probabilities for each possible part independently based on relevant local characteristics, which reduces the amount of data that needs to be processed while maintaining identification accuracy
Solution Approach 2:
The system changes the approach from using extensive database searches to using parameter-based probability calculations. By calculating part probabilities based on key parameters such as orientation angles and specific image features rather than searching through extensive pattern databases, the system significantly reduces data processing time while maintaining identification accuracy
Data Source
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AI summary
An ultrasound diagnostic apparatus has: an image acquiring unit that transmits/receives an ultrasound beam from an ultrasound probe to acquire an ultrasound image; a part probability calculating unit that calculates, for the ultrasound image acquired in accordance with a first imaging condition, a probability that a part included in the ultrasound image is a specific part from at least one of an orientation angle of the ultrasound probe or an analysis result of the ultrasound image; and an imaging condition changing unit that changes, when the probability is greater than or equal to a threshold value, the first imaging condition to a second imaging condition for identifying the part for which the probability has been calculated, in which an ultrasound image is further acquired by using the second imaging condition.