Multiresolution Iterative Reconstruction for ROI Imaging in X-ray CT
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Solution Overview
Problem
Computed tomography (CT) systems face challenges in achieving high-resolution images within a region of interest (ROI) while minimizing truncation artifacts and computational time, especially in clinical applications where rapid image reconstruction is crucial.
Innovation Solution
The method involves partitioning the image and sinogram domains into high- and low-resolution regions, with downsampling of projection data by a pixel-pitch ratio to reduce computational burden and truncation artifacts, allowing for efficient high-resolution imaging within the ROI using a single scan rather than multiple passes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a smaller diameter X-ray beam is focused on the region of interest to achieve higher resolution, then manufacturing precision of the image is improved, but truncation artifacts increase and reliability deteriorates
Solution Approach 1:
The patent divides the image space into multiple regions of interest (ROIs) with different resolutions. The full field of view is segmented into a first ROI at high resolution and a second ROI at lower resolution, allowing high-resolution imaging of critical areas while maintaining lower resolution in less critical areas, thereby reducing truncation artifacts and improving overall image reliability
Solution Approach 2:
The patent applies different resolution qualities to different regions of the image. By assigning high resolution only to specific ROIs that require detailed visualization and lower resolution to surrounding areas, the system optimizes image quality where needed while minimizing the negative effects of truncation in non-critical regions
2Manufacturing precision
If a smaller diameter X-ray beam is used for the region of interest, then manufacturing precision is improved, but loss of information increases
Solution Approach 1:
The patent segments the image into multiple ROIs, ensuring that information is preserved in a downscaled format across the entire field of view while high-resolution information is maintained in critical ROIs. This prevents complete loss of contextual information while achieving high resolution where needed
3Loss of information
If a larger field of view is used for reconstruction, then loss of information is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent applies local quality by reconstructing different regions at different resolutions. The full field of view is maintained to preserve contextual information, while specific ROIs are reconstructed at higher resolution to maintain manufacturing precision in critical areas
4Reliability
If two-pass iterative reconstruction is used to reduce truncation artifacts, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent segments the reconstruction process into multiple resolution levels. By performing iterative reconstruction at a lower resolution first and then refining only the critical ROIs at higher resolution, the system reduces the overall computational time compared to full two-pass reconstruction while maintaining image quality in critical areas
5Manufacturing precision
If high-resolution reconstruction is performed across the entire field of view, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The patent applies local quality by performing high-resolution reconstruction only in specific ROIs rather than across the entire field of view. This significantly reduces reconstruction time while maintaining high manufacturing precision in the critical areas that require detailed visualization
Data Source
AI summary
A method and apparatus is provided to generate a multiresolution image having at least two regions with different pixel pitches. The multiresolution image is reconstructed using projection data having various pixel pitches corresponding to the pixel pitches of the multiresolution image. By using a higher resolution inside regions of interest (ROIs) in both the image and projection domains and lower resolution outside the ROIs, fast image reconstruction can be performed while avoiding truncation artifacts, which result imaging is limited to an ROI excluding attenuation regions. Further, those regions of greater clinical relevance and greater structural variance within the reconstructed images can be selected to be within the ROIs to improve the clinical benefit of the multiresolution image. The multiresolution image can be reconstructed using an iterative reconstruction method in which the high- and low-resolution regions are uniquely evaluated.