Iterative CT Reconstruction for Breathing Motion Artifact Removal
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Solution Overview
Problem
Current medical imaging technologies, particularly CT scans, face challenges in reducing motion-induced artifacts during breathing, which degrades image quality and limits diagnostic capabilities in pulmonology and upper abdominal imaging, especially in patients unable to hold their breath.
Innovation Solution
A method and apparatus that acquire raw CT imaging data, process it by estimating a 3D image, comparing it to actual sinogram data, and iteratively reconstructing the image using a predetermined motion model to remove breathing motion artifacts, effectively producing artifact-free images as if the patient had held their breath.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If CT scanners are made faster to reduce motion artifacts, then scanning speed is improved, but motion-induced artifacts are not eliminated
Solution Approach 1:
The patent implements an iterative reconstruction process where the system continuously compares the reconstructed image against the acquired sinogram data, calculates differences, and updates the image estimate. This feedback loop allows the system to compensate for motion artifacts by repeatedly refining the image reconstruction until convergence, thereby maintaining image quality despite fast scanning speeds that would normally produce motion blur.
Solution Approach 2:
The patent applies a predetermined motion model to the 3D image during the reconstruction process. By pre-characterizing the breathing motion pattern and incorporating it into the reconstruction algorithm beforehand, the system can proactively correct for expected motion artifacts rather than merely reacting to them, thus preserving image quality in fast scans.
2Manufacturing precision
If breath-hold CT is used to eliminate motion artifacts, then image quality is improved, but patient comfort and accessibility deteriorate
Solution Approach 1:
The iterative reconstruction with feedback allows the system to achieve breath-hold quality images from free-breathing data. By continuously refining the image estimate and comparing it against the raw sinogram data, the algorithm compensates for breathing motion without requiring the patient to hold their breath, thus maintaining image quality while improving patient comfort and accessibility.
Solution Approach 2:
The patent changes the reconstruction approach from traditional single-pass methods to iterative reconstruction with motion modeling. This parameter change in the reconstruction algorithm enables the system to handle free-breathing conditions effectively, removing the need for breath-hold requirements while maintaining diagnostic image quality.
3Manufacturing precision
If iterative reconstruction with motion modeling is applied, then motion artifact removal is improved, but computational complexity increases
Solution Approach 1:
The patent uses a predetermined motion model that characterizes breathing patterns in advance. By pre-defining the motion model parameters and incorporating them into the reconstruction process beforehand, the system reduces the computational burden during iterative reconstruction, as it doesn't need to estimate motion parameters from scratch but rather applies known motion characteristics to correct the images.
Data Source
AI summary
A method and apparatus for removing breathing motion artifacts in imaging CT scans is disclosed. The method acquires raw imaging data from a CT scanner, and processes the raw CT imaging data by removing motion-induced artifacts via a motion model. Processing the imaging data may be achieved by initially estimating a 3D image to provide an estimate of raw sinogram image data, comparing the estimate to an actual CT sinogram, determining a difference between the sinograms, and iteratively reconstructing the 3D image by using the difference to alter the 3D image until the sinograms agree, wherein the 3D image moves according to the motion model.