Ultrasound Dynamic Range Adaptation via Histogram CDF Mapping
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Solution Overview
Problem
Existing ultrasound systems struggle to optimally display images due to a fixed, non-adaptive dynamic range, which can result in suboptimal image quality, especially in applications like cardiac and obstetric imaging where fluid representation dominates, leading to excessive black or dark pixels and insufficient white pixels.
Innovation Solution
An adaptive technique that maps the full dynamic range of ultrasound images to a displayed range using a processor configured to generate histograms and cumulative density functions (CDFs), allowing for dynamic adjustment of the displayed range based on specific pixel value distributions, with user controls for fine-tuning and depth-dependent analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed, non-adaptive dynamic range is used for display, then the system is simple to operate, but the image quality is suboptimal with excessive black pixels and insufficient white pixels
Solution Approach 1:
The system performs self-adjustment by automatically analyzing the pixel value distribution and adapting the dynamic range mapping without requiring manual intervention. The processor generates histograms and CDFs, then autonomously determines the optimal mapping parameters based on the detected echo signal characteristics, allowing the system to serve itself in optimizing display parameters.
Solution Approach 2:
The dynamic range mapping transitions from a fixed, static configuration to a dynamic, adaptive system that automatically adjusts based on the actual pixel value distribution in the image data. The mapping parameters are no longer fixed but are dynamically determined through histogram analysis and CDF-based optimization for each imaging scenario.
2Device complexity
If a fixed dynamic range is used, then the device complexity is low, but the image display is suboptimal for various clinical applications
Solution Approach 1:
The system implements dynamic adaptability by automatically adjusting the dynamic range mapping parameters based on the actual distribution of pixel values in the acquired image data. This allows the same system to optimally display images across various clinical applications (cardiac, obstetric, etc.) without requiring multiple fixed configurations or manual reconfiguration.
Solution Approach 2:
The system changes the display parameters (dynamic range mapping parameters) based on the analyzed pixel value distribution. By modifying the mapping parameters according to the histogram and CDF analysis, the system achieves versatility across different clinical applications while maintaining a relatively simple overall architecture.
3Ease of operation
If manual control of log scale is used, then the system is easy to understand, but the displayed dynamic range does not adapt to varying tissue echo strengths and clutter
Solution Approach 1:
The system implements feedback by analyzing the actual pixel value distribution from the image data and using this information to automatically adjust the dynamic range mapping parameters. The feedback loop involves generating histograms, computing CDFs, and using the detected distribution characteristics to determine the optimal mapping, allowing the system to adapt to varying tissue echo strengths and clutter conditions.
Solution Approach 2:
The system performs self-optimization by automatically determining the appropriate dynamic range mapping based on the characteristics of the acquired image data. Rather than requiring manual adjustment for each imaging scenario, the system autonomously analyzes the pixel distribution and configures the mapping parameters to achieve optimal display quality.
Data Source
AI summary
An ultrasound imaging system according to the present disclosure may include an ultrasound probe, a display unit, and a processor configured to receive source image data having a first dynamic range, wherein the source image data comprises log compressed echo intensity values based on the ultrasound echoes detected by the ultrasound probe, generate a histogram of at least a portion of source image data, generate a cumulative density function for the histogram, receive an indication of at least two points on the cumulative density function (CDF), and cause the display unit to display an ultrasound image representative of the source image data displayed in accordance with the second dynamic range.