CT Image Reconstruction Using Multi-FOV Segmentation
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Solution Overview
Problem
Current imaging systems face challenges in reconstructing high-resolution images within large fields of view, particularly for moving subjects like the heart, where large fields of view result in lower image quality due to motion artifacts and unclear artery visibility.
Innovation Solution
The method involves determining multiple fields of view and using a weighting function to reconstruct images from different portions of scan data, generating a third image by combining the first and second images, thereby enhancing resolution and clarity within a larger field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a large field of view is used for image reconstruction, then the coverage area increases and more anatomical structures are visible, but the image resolution deteriorates and motion artifacts increase
Solution Approach 1:
The patent divides the scan data into multiple portions, each corresponding to a different field of view size. A first portion of scan data is used to reconstruct a first image with a first field of view, while a second portion is used to reconstruct a second image with a second field of view. This segmentation allows different regions to be optimized for different resolution requirements, resolving the contradiction between large coverage and high resolution.
2Area of stationary object
If a large field of view is used for image reconstruction, then the coverage area increases, but motion artifacts increase and artery clarity deteriorates
Solution Approach 1:
The patent applies different reconstruction strategies to different portions of scan data based on local quality requirements. By reconstructing a first image from a first portion of scan data and a second image from a second portion, then combining them, the system ensures that critical regions (such as heart arteries) maintain high reliability and clarity while the overall field of view remains large.
3Measurement precision
If a small field of view is used for image reconstruction, then the image resolution improves, but the coverage area decreases and clinical demands are not met
Solution Approach 1:
The patent merges a first image reconstructed from a first portion of scan data with a second image reconstructed from a second portion of scan data to generate a third image. This combining process allows the final image to simultaneously achieve high resolution in critical areas and large field of view coverage, satisfying both resolution requirements and clinical demands for comprehensive anatomical visualization.
Data Source
AI summary
A method for reconstructing an image may include obtaining scan data relating to a subject. The method may also include determining a first field of view (FOV) and determining a second FOV. The method may further include reconstructing a first image based on a first portion of the scan data corresponding to the first field of view, and reconstructing a second image based on a second portion of the scan data corresponding to the second field of view. The method may also include generating a third image based on the first image and the second image.