CT Noise Map Estimation Using Multiple View Sets
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Solution Overview
Problem
Existing noise map estimation methods for CT images are limited by requiring only two exclusive sets of views, which restricts the generalization of noise estimation, and do not effectively utilize the full potential of CT image data.
Innovation Solution
The proposed method estimates noise maps using three sets of independent views, two sets of correlated views, and two sets of unequal numbered views, allowing for more flexible and accurate noise estimation by reconstructing images from these varied view sets and applying specific mathematical relationships to calculate variance maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only two exclusive sets of views are used for noise map estimation, then the reconstruction procedure is simplified, but the generalization capability and accuracy of noise estimation are limited
Solution Approach 1:
The patent generalizes the noise map estimation method to work with multiple types of view sets (independent views, correlated views, equal numbered views, unequal numbered views), making the method universally applicable to different CT scanning configurations while maintaining accurate noise estimation
Solution Approach 2:
The patent segments the projection views into different sets (first set, second set, third set) that can be independently configured, allowing flexible combination of views for noise estimation while separating the noise estimation function from the main reconstruction process
2Power
If two sets of views are used for noise map estimation, then the computational load is reduced, but the utilization of available CT image data is insufficient
Solution Approach 1:
The patent merges multiple view sets (including all available projection views) into the noise estimation process by combining images reconstructed from different view configurations, thereby utilizing the full available data while distributing computational work across multiple independent estimations
3Ease of operation
If exclusive independent views are used for noise estimation, then the noise map estimation is simpler, but the robustness across different view configurations is reduced
Solution Approach 1:
The patent introduces dynamic adaptability by allowing the noise estimation method to automatically adjust to different view configurations (independent or correlated views, equal or unequal numbering) while maintaining a consistent computational framework, thereby achieving both simplicity and robustness
Data Source
AI summary
Noise map for CT images have been estimated by generalizing the prior art even-and-odd views approach. One example is to estimate a noise map from images reconstructed from three sets of independent views. A second example is to estimate a noise map from images reconstructed by using two sets of correlated views. A third example is to estimate a noise map from noise map from two images reconstructed from two sets of independent views while the number of views in each set is unequal. Physical phantom data were employed to validate our proposed noise map estimation methods. In comparison to the existing method, our alternative methods yield reasonably accurate noise map estimation.