Motion Correction for Medical Image Data Using Localizer Analysis
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Solution Overview
Problem
Current PET image data processing is hindered by motion degradation during acquisition, particularly respiratory motion, which requires computationally intensive correction methods and manual operator selection of anatomical regions, making widespread use of motion correction complicated and time-consuming.
Innovation Solution
An automated framework that identifies anatomical ranges for motion correction using localizer images, integrating motion correction seamlessly into standard imaging protocols without user interaction or additional hardware, enabling efficient reconstruction of motion-corrected image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion correction is applied to PET image data, then image quality is improved, but computational intensity increases significantly
Solution Approach 1:
The patent applies motion correction selectively only to anatomical regions where motion is detected in localizer images, rather than processing the entire image dataset. This localized approach maintains image quality improvement in motion-affected regions while significantly reducing the computational burden compared to full-volume motion correction.
Solution Approach 2:
The patent divides the PET image data into multiple anatomical regions or volumes based on motion detection results. Motion correction is applied independently to each segment, allowing the system to process only the necessary portions of the data, thereby reducing overall computational intensity while maintaining image quality where needed.
2Measurement precision
If manual operator selection of anatomical regions is used for motion correction, then correction accuracy is improved, but time consumption and operator dependency increase
Solution Approach 1:
The patent implements automated detection of anatomical regions requiring motion correction using analysis of localizer images. The system independently identifies motion-affected regions without requiring manual operator selection, thereby eliminating operator dependency and significantly reducing the time required to initiate motion correction while maintaining accurate region identification.
3Ease of manufacture
If motion correction is applied to regions not subject to motion, then image processing is simplified, but unwanted noise is introduced
Solution Approach 1:
The patent applies motion correction selectively only to anatomical regions where motion is actually detected in localizer images. By identifying and processing only the specific regions affected by motion rather than applying correction uniformly across all regions, the system maintains processing simplicity while avoiding the introduction of unwanted noise in static regions.
Data Source
AI summary
A framework for motion correction in medical image data. In accordance with one aspect, one or more anatomical ranges where motion is expected are identified in a localizer image of a subject. Image reconstruction with motion correction may be performed based on medical image data within the one or more anatomical ranges to generate motion corrected image data. The motion corrected image data may then be combined with non-motion corrected image data to generate final image data.