Radiographic Image Analysis Using Body Thickness Distribution Estimation
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Solution Overview
Problem
Existing methods for determining image processing and imaging conditions based on subject body thickness often rely on a single representative value, which is insufficient to accurately account for variations in thickness across different positions, leading to suboptimal image quality.
Innovation Solution
A radiographic image analysis device and method that estimates body thickness distribution by comparing characteristic information from a subject image to a database of model images with associated thickness distributions, allowing for precise determination of thickness variations across the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single representative value is used to represent body thickness, then the device complexity is reduced and ease of operation is improved, but the measurement precision and reliability of image quality improvement are degraded
Solution Approach 1:
The patent segments the body thickness measurement into multiple discrete thickness values corresponding to different anatomical regions (e.g., anterior, lateral, posterior). Instead of using a single representative value, the system divides the measurement into region-specific values that can be independently determined and applied, thereby improving measurement precision while maintaining operational simplicity through automated region identification.
Solution Approach 2:
The patent applies local quality by assigning different thickness values to different spatial regions of the subject's body. Each region receives a thickness value specific to its anatomical characteristics, allowing image processing conditions to be optimized locally rather than uniformly across the entire image. This resolves the contradiction by providing high measurement precision where needed while keeping the overall system easy to operate through automated regional analysis.
2Device complexity
If a single representative value is used for body thickness, then the device complexity is reduced, but the reliability of suppressing scattered X-ray effects is degraded
Solution Approach 1:
The system segments the body into multiple regions with distinct thickness characteristics, determining a separate thickness value for each region. This segmentation approach improves reliability by accounting for regional variations in X-ray attenuation and scattered radiation effects, while device complexity remains manageable through automated region detection and classification algorithms.
Solution Approach 2:
The patent changes the parameter representation from a single thickness value to multiple region-specific thickness values. This parameter change enables more accurate modeling of X-ray interaction with different body regions, improving the reliability of scattered X-ray suppression. The complexity increase is offset by using standardized parameter sets that can be automatically selected based on detected anatomical features.
3Measurement precision
If multiple model images with different thickness distributions are used, then the measurement precision of body thickness distribution is improved, but the device complexity and loss of information increase
Solution Approach 1:
The patent creates a universal set of model images representing different body thickness distributions that can be applied to multiple subjects and imaging scenarios. This multi-functional model library allows the system to achieve high measurement precision by selecting the most appropriate model for each subject, while managing device complexity through a standardized, reusable model set rather than requiring custom models for each case.
Solution Approach 2:
The system uses copied model images representing typical body thickness distributions as references for determining actual subject thickness. By comparing the subject image against these pre-established models, the system achieves high measurement precision without requiring complex real-time calculations, thereby managing device complexity while maintaining accuracy.
4Reliability
If multiple model images with different thickness distributions are used, then the reliability of image processing is improved, but the loss of information increases
Solution Approach 1:
The patent segments the body thickness information into multiple discrete regional values, each representing a specific anatomical region. This segmentation improves reliability by preserving region-specific thickness information that would be lost in a single representative value, while managing information loss through systematic region classification and standardized data representation.
Solution Approach 2:
The system applies local quality by maintaining distinct thickness values for different spatial regions rather than using a uniform value. This approach improves reliability by preserving local thickness variations that are critical for accurate image processing, while minimizing overall information loss through efficient encoding of regional characteristics.
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
This approach enables accurate determination of body thickness distribution, improving image quality by effectively accounting for thickness variations and enhancing the suppression of scattered X-ray effects.
Implementation Method 1
the influence of the scattering of radiation or a reduction in the transmissivity of radiation in the subject increases as the thickness of the subject increases
Implementation Method 2
When a radiographic image of a subject is captured by radiation passing through the subject
Data Source
AI summary
A subject image is acquired. Model information, in which a model image captured by irradiating each of a plurality of models different from the subject with radiation is associated with a body thickness distribution of the model in the model image is acquired for each of the plurality of models. Characteristic information indicating characteristics of the subject image is acquired. Characteristic information indicating the characteristics of each of the plurality of model images is acquired, on the basis of the plurality of model information items. The model image having characteristic information similar to the characteristic information of the subject image is specified. The body thickness distribution associated with the specified model image is determined as the body thickness distribution of the subject image.