Real-time Motion Tracking via Photon Singles Rate Analysis
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Solution Overview
Problem
Current data-driven techniques for real-time cardio-respiratory motion tracking in PET imaging are not suitable for routine use due to high data processing requirements, making them inefficient for extracting motion signals during daily scans.
Innovation Solution
The development of real-time motion-tracking techniques that utilize intrinsic photon counting capabilities to construct time-count curves or count-rate time series directly from raw photon-events data, allowing for the extraction of cardio-respiratory motion signals without external devices, and can be integrated into existing photon imaging systems as software or hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data-driven techniques are used for motion correction in PET imaging, then motion artifacts are reduced, but data processing time and computational power requirements increase substantially
Solution Approach 1:
The patent extracts only the essential motion-related information (gating signals) from the raw photon events data, rather than processing the entire dataset. By using time-count curves and count-rate time series derived from singles data, the system isolates the critical motion signals needed for correction, significantly reducing computational burden while maintaining accuracy.
Solution Approach 2:
The system performs motion tracking preliminarily during the data acquisition phase by continuously monitoring time-count curves and count rates. This preliminary extraction of motion signals allows for real-time gating without requiring intensive post-processing, as the motion information is captured concurrently with the imaging data.
2Measurement precision
If external monitoring devices (ECG, breathing belts) are used for cardio-respiratory motion tracking, then motion signals are obtained, but device complexity and additional hardware requirements increase
Solution Approach 1:
The PET scanner itself serves the dual function of both imaging and motion tracking. The system utilizes its intrinsic photon counting capabilities to generate time-count curves and count-rate time series from singles data, allowing the imaging device to self-monitor cardio-respiratory motions without requiring separate external monitoring equipment.
Solution Approach 2:
The patent makes the PET scanner multi-functional by enabling it to simultaneously perform imaging and motion tracking. The same detector system that captures photon events for imaging also monitors count rate variations that correlate with cardio-respiratory motions, eliminating the need for dedicated external monitoring devices.
3Device complexity
If conventional external monitoring techniques are replaced by intrinsic photon counting methods, then device complexity is reduced, but measurement precision may be compromised
Solution Approach 1:
The system changes the measurement parameter from direct physical sensing (as in external devices) to indirect inference through photon count rate analysis. By monitoring temporal variations in singles count rates and constructing time-count curves, the system extracts motion signals based on the physiological modulation of photon emission, achieving accurate motion tracking through parameter transformation rather than direct measurement.
Data Source
AI summary
Various techniques are provided for performing real-time subject-motion-tracking during photon imaging by applying various data processing techniques on raw photon-events data generated by photon imaging scanners. In one aspect, a process of performing real-time subject-motion tracking during photon imaging begins by receiving multiple channels of raw singles-event data from a set of detector groups of the photon scanner while scanning a live subject. For each received channel of raw singles-event data, a singles-rate time series is generated based on a predetermined temporal resolution. Next, the set of singles-rate time series corresponding to the set of detector groups is combined to generate an overall singles-rate time series. Subsequently, the overall singles-rate time series is processed to extract in real-time one or more motion signals corresponding to one or more physiological motions of the live subject while the live subject is being scanned.