Radiographic Image Processing Apparatus S/N Optimization
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Solution Overview
Problem
Radiographic images often suffer from noise and varying contrast due to radiography conditions, subject conditions, and detector characteristics, leading to an unsuitable signal-to-noise ratio (S/N) when noise removal processing is based solely on body thickness.
Innovation Solution
A radiographic image processing apparatus that obtains radiographic images, gathers information on radiography conditions, subject conditions, detector characteristics, and body thickness, and adjusts the signal-to-noise ratio by performing noise removal and contrast adjustment processing to achieve an optimal S/N based on these factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If noise removal processing is performed based solely on body thickness, then processing simplicity is maintained, but the signal-to-noise ratio becomes inappropriate due to variations in radiography conditions, subject conditions, and detector characteristics
Solution Approach 1:
The patent applies parameter changes by introducing multiple variables (radiography conditions, subject conditions, detector characteristics) to dynamically adjust noise removal processing. Instead of using a fixed parameter (body thickness alone), the system modifies processing parameters based on combinations of multiple factors, enabling appropriate S/N ratio adjustment for diverse imaging scenarios
Solution Approach 2:
The patent implements dynamics by making noise removal processing adaptive rather than static. The processing automatically adjusts based on real-time input parameters including radiography conditions, subject conditions, and detector characteristics, allowing the system to respond dynamically to varying imaging conditions and maintain optimal S/N ratio
2Measurement precision
If multiple parameters (radiography conditions, subject conditions, detector characteristics) are considered for noise removal, then appropriate S/N ratio is achieved, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex noise removal process into distinct functional modules: radiography condition analysis, subject condition analysis, detector characteristic analysis, and integrated processing. Each module handles specific parameters independently, then combines results to achieve appropriate S/N ratio without overwhelming system complexity
Solution Approach 2:
The patent implements universality by creating a multi-functional processing system that simultaneously handles radiography conditions, subject conditions, and detector characteristics. The unified processing apparatus performs multiple functions (noise removal, contrast adjustment, S/N optimization) through integrated analysis of all input parameters
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 the production of high-quality radiographic images with an appropriate S/N ratio, suitable for diagnosis, by tailoring noise removal and contrast adjustment to the specific conditions of the radiography, subject, and detector used.
Implementation Method 1
detecting the radiation passed through the subject by a radiation detector
Data Source
AI summary
An image obtainment unit obtains a radiographic image radiographed by irradiating a subject with radiation. A first information obtainment unit obtains information about at least one of a radiography condition during radiography of the subject, a subject condition and detector characteristics, which are characteristics of the radiation detector. A second information obtainment unit obtains body thickness information representing the body thickness of the subject. A target S/N setting unit sets a target S/N of the radiographic image based on the body thickness information and the information about at least one of the radiography condition, the subject condition and the detector characteristics. An image processing unit corrects the S/N of the radiographic image to the target S/N by performing, on the radiographic image, noise removal processing.