CT Image Movement Artifact Correction via Block Optimization
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Solution Overview
Problem
Existing computed tomography (CT) image reconstruction methods fail to effectively correct movement artifacts, particularly for complex patient movements, and are computationally intensive, limiting their applicability and efficiency.
Innovation Solution
A method that uses global optimization to determine the average position of an examination area and divides projection images into blocks to estimate movement, employing a gradient descent method and user-defined criteria for block formation, allowing for efficient correction of movement artifacts by focusing on significant areas and reducing computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If feature-based methods with global optimization are used to correct movement artifacts, then manufacturing precision of image reconstruction is improved, but device complexity and computation time increase
Solution Approach 1:
The patent divides the set of all projection images into multiple blocks, where each block contains a subset of projection images. Movement estimation is performed separately for each block using optimization methods, rather than processing all projections globally. This segmentation reduces the computational complexity and memory requirements while maintaining correction precision for complex movement patterns.
Solution Approach 2:
The patent applies optimization methods selectively to estimate movement parameters for each block of projections rather than performing exhaustive global optimization on all projections. This partial action approach achieves sufficient correction precision for clinical purposes while significantly reducing computation time and resource requirements.
2Ease of operation
If projection-based methods are used for movement correction, then ease of operation is improved, but measurement precision deteriorates for complex movements
Solution Approach 1:
The patent segments the projection data into multiple blocks and applies optimization-based movement estimation to each block. This allows the method to handle complex non-rigid movements that single-projection methods cannot capture, improving measurement precision while maintaining operational simplicity through automated block processing.
Solution Approach 2:
The patent employs dynamic optimization methods that adapt to the specific movement patterns present in each block of projections. By allowing movement parameters to vary across different blocks, the method accurately captures complex temporal variations in patient movement that static or single-projection methods miss.
Data Source
AI summary
A method for correction of movement artifacts in a computed tomography image that is reconstructed from a plurality of computed tomography projection images is provided. Using all projection images of the plurality of computed tomography projection images, an average position of an examination area of an examination object in the reconstructed image volume is determined by a global optimization method. With the aid of the at least one image volume block that is formed from predeterminable projection images, the movement of the examination area of the examination object in the at least one image volume block is estimated by an optimization method. A corresponding device for correction of movement artifacts in a computed tomography image is also provided.