Adaptive High-Frequency Enhancement for X-ray CT Spatial Resolution
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Solution Overview
Problem
Conventional X-ray CT image reconstruction techniques face a trade-off between spatial resolution and noise level, where maximizing spatial resolution leads to increased noise, and existing reconstruction functions do not fully utilize the potential spatial resolution of projection data, especially in regions with fine structures like auditory ossicles, while unnecessarily increasing noise in areas that do not require high spatial resolution.
Innovation Solution
An image processing apparatus that acquires typical pixel values and calculates variance index values in specific regions, determining enhancement degrees based on these values to perform high-frequency enhancement processing, thereby improving spatial resolution without unnecessarily increasing noise. This involves multiple enhancement degree determination devices that adjust processing based on relations between pixel values, variance ranges, and reconstruction functions to selectively enhance high-frequency components in regions needing higher resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a reconstruction function that strongly enhances high-frequency components is used to maximize spatial resolution, then spatial resolution is improved, but noise level increases sharply
Solution Approach 1:
The patent applies different enhancement strategies to different regions of the image based on their characteristics. High-frequency enhancement is applied strongly to regions with fine structures (like auditory ossicles) while being suppressed or not applied to regions with soft tissues. This local differentiation allows maximizing spatial resolution where needed without unnecessarily increasing noise in regions where it is not required.
Solution Approach 2:
The patent dynamically adjusts the enhancement degree parameter based on the characteristics of each region. By calculating variance index values and typical pixel values, the system determines appropriate enhancement degrees for each region, changing the enhancement parameter from a fixed value to a variable one that adapts to local image characteristics.
2Measurement precision
If a reconstruction function adjusted for high spatial resolution is applied uniformly across the entire image, then spatial resolution is improved in regions requiring it, but noise is increased needlessly in regions that do not require high spatial resolution
Solution Approach 1:
The patent divides the image into different regions and applies different enhancement strategies to each region based on its characteristics. Regions with fine structures receive strong high-frequency enhancement, while regions with soft tissues receive suppressed or no enhancement. This local differentiation eliminates unnecessary noise increase in regions where high spatial resolution is not required.
Solution Approach 2:
The patent segments the image into different regions based on variance index values and typical pixel values. By identifying distinct regions (fine structure regions vs. soft tissue regions), the system can apply different processing strategies to each segment, avoiding uniform application of enhancement that would cause unnecessary noise elsewhere.
3Object-affected harmful factors
If conventional reconstruction functions are used, then noise level is kept within a durable range for practical use, but potential spatial resolution of projection data is not fully utilized
Solution Approach 1:
The patent transforms the static, fixed enhancement degree of conventional reconstruction functions into a dynamic, variable enhancement degree that adapts to each region's characteristics. The enhancement degree is calculated based on variance index values and typical pixel values, allowing the system to optimize spatial resolution potential in each region while maintaining acceptable noise levels.
Solution Approach 2:
The patent changes the enhancement degree parameter from a fixed value in conventional functions to a variable parameter that is calculated based on regional characteristics. This allows the system to extract maximum spatial resolution potential from projection data in regions where it is needed while keeping noise levels acceptable through adaptive parameter adjustment.
Data Source
AI summary
An image processing apparatus is provided. The image processing apparatus includes an acquiring device configured to acquire a typical pixel value corresponding to a noted region in an image, a calculating device configured to calculated index values of variances in pixel values in the noted region or in both the noted region and a region adjacent to the noted region, a first enhancement degree determination device configured to determine an enhancement degree according to the acquired typical pixel value and each of the calculated index values, and an image processing device configured to perform high-frequency enhancement processing on the noted region, based on the enhancement degree determined by the first enhancement degree determination device.