Medical Image Reconstruction Using Motion-Adaptive Prior Images
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Solution Overview
Problem
In medical imaging, particularly in CT scans, images reconstructed from small scanning angle ranges have high temporal resolution but may lack details due to insufficient data, while images from large scanning angle ranges provide more details but with poor temporal resolution and motion artifacts, degrading the quality of reconstructed images.
Innovation Solution
A system and method that utilize prior images from large scanning angle ranges to supplement target images from small scanning angle ranges by determining a restriction factor based on motion characteristics, allowing selective application of prior image elements to improve temporal resolution and image quality, especially in regions with low or no motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If images are reconstructed from large scanning angle ranges, then image details are improved, but temporal resolution deteriorates and motion artifacts increase
Solution Approach 1:
The image is divided into multiple regions based on motion characteristics. Motion regions are reconstructed using scanning data with high temporal resolution, while static regions are reconstructed using prior images with more complete scanning data. This segmentation allows different parts of the image to use different reconstruction strategies optimized for their specific needs.
Solution Approach 2:
Different reconstruction qualities are applied to different regions of the image. Static regions receive high-quality reconstruction from prior images with complete scanning angle ranges, while motion regions receive reconstruction optimized for temporal resolution. This local quality approach ensures each region gets the appropriate level of detail without compromising overall image quality.
2Loss of time
If images are reconstructed from small scanning angle ranges, then temporal resolution is improved, but image details are insufficient
Solution Approach 1:
Prior images are pre-acquired with complete scanning angle ranges before the actual scanning process. These prior images contain comprehensive anatomical details that can be used to supplement the current scanning data. By having this information prepared in advance, the system can quickly reconstruct motion regions without losing temporal resolution while still providing complete anatomical context.
Solution Approach 2:
The prior image acts as an intermediary that bridges the gap between incomplete current scanning data and complete anatomical information. The restriction factor selectively combines information from the prior image with current scanning data, using the prior image to fill in anatomical details in static regions while preserving temporal accuracy in motion regions.
3Measurement precision
If prior images are applied to reconstruct target images, then image quality is improved, but motion artifacts increase in motion regions
Solution Approach 1:
The restriction factor is dynamically adjusted based on motion characteristics detected in the image. Regions with high motion content receive lower weights for prior image contribution, while static regions receive higher weights. This dynamic adaptation ensures that prior images are used appropriately only where they improve quality without introducing motion artifacts.
Solution Approach 2:
The system analyzes motion characteristics of the subject and uses this feedback to determine the restriction factor. By continuously assessing motion levels in different regions, the system can adaptively control the contribution of prior images, preventing motion artifacts in moving regions while maximizing quality improvement in static regions.
Data Source
AI summary
The present disclosure relates to systems and methods for medical imaging. The method may include obtain scanning data and at least one prior image of a subject. The method may include determining a restriction factor for each of the at least one prior image based on the scanning data. The restriction factor of the each prior image may relate to a motion of the subject corresponding to the scanning data. The method may include determining an objective function based on the restriction factor. The method may also include reconstructing, using the objective function, a target image of the subject based on the scanning data and the at least one prior image.