Ultrasound Tissue Detection via Spatial Frequency Analysis
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Solution Overview
Problem
Conventional ultrasonic diagnosing devices rely on operator experience to distinguish muscular tissue from subcutaneous tissue, and the detection accuracy is affected by age-related variations in echo signal amplitudes, making precise detection challenging.
Innovation Solution
An ultrasonic body tissue detecting device with a transmission/reception unit, two-dimensional data acquisition unit, spatial frequency distribution calculation unit, and determination unit that converts echo signals into spatial frequency distributions to automatically differentiate between muscular and subcutaneous tissues based on numeric values and threshold comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual observation of two-dimensional echo image by operator is used, then device complexity is low, but measurement precision deteriorates due to dependence on operator experience
Solution Approach 1:
The patent replaces the manual visual observation mechanism with an automated image processing system that calculates luminosity distribution patterns and compares them against reference patterns. This substitution of mechanical/manual operations with automated computational methods resolves the contradiction by eliminating operator experience dependence while maintaining system feasibility through software-based analysis.
Solution Approach 2:
The patent transforms the detection approach by changing from direct visual observation to quantitative analysis of luminosity distribution patterns. By converting qualitative visual assessment into quantitative parameter comparison (luminosity distributions), the system achieves higher measurement precision through objective numerical analysis rather than subjective visual evaluation.
2Measurement precision
If conventional luminosity distribution pattern observation is used, then device complexity is low, but measurement precision deteriorates due to age-related amplitude variations
Solution Approach 1:
The patent replaces direct observation of absolute luminosity values with automated calculation and comparison of luminosity distribution patterns. This substitution eliminates the influence of age-related amplitude variations by focusing on relative pattern characteristics rather than absolute values, achieving age-invariant detection through computational analysis.
Solution Approach 2:
The patent changes the detection parameter from absolute luminosity amplitude to luminosity distribution pattern. By transforming the measurement from amplitude-based to pattern-based analysis, the system becomes insensitive to age-related amplitude changes while maintaining the ability to distinguish muscular tissue boundaries through pattern recognition.
3Measurement precision
If automated detection is implemented, then measurement precision improves, but device complexity increases due to spatial frequency conversion
Solution Approach 1:
The patent introduces spatial frequency distribution as an intermediary representation between the original echo signals and the final detection result. This intermediary transformation enables precise extraction of tissue boundary information by converting spatial variations into frequency domain characteristics, resolving the contradiction through structured data transformation.
Solution Approach 2:
The patent replaces direct spatial analysis with frequency domain analysis through spatial frequency conversion. This substitution transforms the detection mechanism from direct image interpretation to spectral analysis, enabling automated precision detection through mathematical transformation and pattern comparison.
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
Enables precise and automatic detection of muscular and subcutaneous tissues, independent of operator experience and age-related amplitude variations, ensuring high precision and consistency.
Implementation Method 1
transmits an ultrasonic signal into a body of a sample and receives an echo signal of the ultrasonic signal
Data Source
AI summary
A body tissue to be detected is automatically detected certainly with high precision. An ultrasonic body tissue detecting device may include a transmission/reception unit, a two-dimensional data acquisition unit, a spatial frequency distribution calculation unit and a determination unit. The transmission/reception unit may transmit an ultrasonic signal into a body of a sample and receive an echo signal of the ultrasonic signal. The two-dimensional data acquisition unit may form two-dimensional echo image in a transmitting direction of the ultrasonic signal and in a scanning direction. The spatial frequency distribution calculation unit may perform a spatial frequency conversion of the two-dimensional echo image and calculate a spatial frequency distribution for a determining position. The determination unit may determine whether the determining position is the body tissue to be detected based on a distribution of amplitude in the transmitting direction of the ultrasonic signal and a distribution of amplitude in the scanning direction of the spatial frequency distribution.