Locally Adaptive Gating for ECT Image Reconstruction
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Solution Overview
Problem
Conventional gating approaches for Emission Computed Tomography (ECT) imaging are inadequate for total-body PET scanners, as they divide data into frames based on motion phases, which is not applicable to regions of the body that do not experience significant motion, leading to over-gating and motion blur in images.
Innovation Solution
The system employs locally adaptive gating, determining different gate numbers for various spatial points based on their specific motion amplitudes, reducing motion blur while minimizing noise, by dividing the ECT data into sections that correspond to the motion characteristics of each region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a conventional gating approach is used to reduce motion blur, then motion blur is reduced in moving regions, but over-gating occurs in non-moving regions leading to increased noise
Solution Approach 1:
The patent applies different gate numbers to different spatial regions based on their motion characteristics. Motion amplitudes are calculated for each spatial point, and gate numbers are assigned locally according to these amplitudes. This ensures that regions with high motion receive appropriate gating to reduce motion blur, while regions with low motion use fewer gates to minimize noise, thereby resolving the contradiction between image resolution and noise level.
Solution Approach 2:
The gating parameter (gate number) is made dynamic and adaptive rather than fixed. The system calculates motion amplitudes for each spatial point and adjusts the gate number accordingly. This dynamic adaptation allows the gating strategy to respond to local motion characteristics, preventing over-gating in static regions while adequately addressing motion blur in moving regions.
2Manufacturing precision
If data is divided into multiple frames for gating, then motion blur is reduced, but the complexity of data processing increases
Solution Approach 1:
The patent segments the data division process by spatial regions rather than uniformly across the entire field of view. Each spatial point is evaluated individually for its motion amplitude, and data is divided into frames only where necessary. This selective segmentation reduces the overall complexity of data processing while maintaining motion blur reduction in regions where it is needed.
Solution Approach 2:
Different gating strategies are applied to different spatial regions based on their motion characteristics. Regions with significant motion receive multi-frame gating processing, while regions with minimal motion use simpler processing. This local differentiation reduces the overall computational complexity while effectively addressing motion blur in problematic areas.
3Ease of operation
If uniform gate numbers are applied to all regions, then implementation is simple, but regions without significant motion suffer from over-gating
Solution Approach 1:
The gate number parameter is changed from a uniform value applied to all regions to a spatially varying parameter determined by local motion amplitudes. The system calculates motion amplitudes for each spatial point and assigns gate numbers accordingly. This parameter change maintains ease of implementation through automated calculation while preventing over-gating in regions without significant motion.
Solution Approach 2:
The system automatically determines appropriate gate numbers for each spatial region based on calculated motion amplitudes, without requiring manual intervention or complex configuration. The motion amplitude calculations and gate number assignments are performed autonomously by the processing system, maintaining simplicity while adapting to local conditions.
Data Source
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AI summary
The present disclosure relates to systems and methods for reconstructing an Emission Computed Tomography (ECT) image. The systems, having at least one machine each of which has at least one processor and storage, may perform the methods to obtain ECT projection data, the ECT projection data corresponding to a plurality of voxels; determine a plurality of gate numbers for the plurality of voxels, the plurality of gate numbers relating to motion information of the plurality of voxels; and reconstruct an ECT image based on the ECT projection data and the plurality of gate numbers.