Dynamic Acquisition Time Adjustment for Multi-Modality Image Registration
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Solution Overview
Problem
Current image reconstruction methods in emission computed tomography (ECT) struggle with synchronizing acquisition time periods across different modalities, leading to inaccurate registration and fusion of images, particularly in multi-modality scans like PET-MRI, where inconsistent reconstruction ranges result in suboptimal diagnostic accuracy.
Innovation Solution
A system and method that dynamically adjust acquisition time periods based on real-time acquisition curves during scans, allowing for consistent reconstruction ranges with user input and automatic modification to match the timing of second modality scans, enabling accurate registration and fusion of images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acquisition time periods are fixed for each modality independently, then the scan process is simple to operate, but image registration accuracy deteriorates due to inconsistent reconstruction ranges
Solution Approach 1:
The system displays acquisition curves in real-time during the scan process, providing visual feedback to operators about the current acquisition status and timing. This allows operators to make informed adjustments to acquisition time periods while maintaining accurate registration, resolving the contradiction between operational simplicity and registration precision.
Solution Approach 2:
The patent implements dynamic adjustment of acquisition time periods based on real-time acquisition curves. Instead of fixed time periods, the system allows flexible modification of acquisition windows to match the actual timing of physiological processes and tracer kinetics, thereby improving image registration accuracy while maintaining user-friendly operation through visual guidance.
2Manufacturing precision
If acquisition time periods are adjusted dynamically to match tracer kinetics, then image quality improves, but the complexity of determining optimal time periods increases
Solution Approach 1:
The system automatically generates and displays acquisition curves based on real-time count rate data, enabling the scan system to self-regulate the acquisition timing. The curves provide visual guidance that helps operators determine optimal acquisition time periods without requiring complex manual calculations or external references, thus improving image quality while limiting complexity growth.
Solution Approach 2:
The acquisition curve serves as an intermediary tool that translates complex tracer kinetics and count rate variations into visual information that operators can easily interpret. This intermediary representation simplifies the determination of optimal acquisition time periods by providing intuitive visual cues about when to acquire data for best image quality.
3Adaptability or versatility
If real-time acquisition curves are displayed during scanning, then operator control over acquisition timing improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent replaces complex mechanical timing mechanisms with software-based real-time data processing and visualization. Instead of using hardware timers and fixed acquisition sequences, the system processes count rate data in real-time to generate acquisition curves, providing flexible timing control through computational methods that are more adaptable and easier to modify than mechanical systems.
Data Source
AI summary
A method may include obtaining a first acquisition time period related to a scan of a first modality performed on an object. The method may also include obtaining one or more second acquisition time periods related to a scan of a second modality performed on the object. The method may also include obtaining, based on the first acquisition time period and the one or more second acquisition time periods, target data of the object acquired in the scan of the first modality. The method may also include generating one or more target images of the object based on the target data.