Variable Radial Sinogram Dimensions for PET Data Reduction
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Solution Overview
Problem
The increase in axial field of view of PET scanners leads to challenges in data acquisition, storage, and computational demands, with steeper axial angles reducing signal quality due to scattering, attenuation, and increased parallax effects, while traditional methods of limiting coincidence data fail to account for varying radial dimensions.
Innovation Solution
A method and system for limiting coincidence data in PET scanners by allowing a variable radial dimension size within a single dataset, based on axial angle and additional metrics, to select and store only the most statistically useful information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the axial field of view of PET scanners is increased to improve sensitivity, then the number of crystal pairs increases (reaching one hundred billion), but this leads to excessive acquisition demands, data storage demands, and computational demands
Solution Approach 1:
The patent extracts and removes low-quality coincidence data from the dataset based on axial angle criteria. By calculating the axial angle for each coincidence event and comparing it against a threshold, the system selectively discards data that would contribute noise rather than useful signal, thereby reducing the overall data burden while maintaining sensitivity for valuable events
Solution Approach 2:
The patent changes the parameter of data selection by introducing axial angle as a filtering criterion. Instead of uniformly accepting all coincidence events, the system dynamically evaluates each event's axial angle and selectively retains only those within acceptable ranges, transforming the data acquisition strategy from comprehensive to selective
2Reliability
If the number of detector rings is increased to improve sensitivity, then more coincidence events can be detected, but the data storage and computational requirements increase significantly
Solution Approach 1:
The patent extracts only the essential high-quality coincidence data by applying axial angle filtering. This selective extraction reduces the quantity of data that needs to be stored and processed, while preserving the sensitivity benefits of having multiple detector rings by retaining the most informative events
Solution Approach 2:
The patent discards low-quality coincidence data that would consume storage space without contributing meaningful information. By establishing quality thresholds based on axial angle, the system recovers only the valuable subset of data needed for accurate image reconstruction
3Reliability
If coincidence data from all detector rings is acquired to improve sensitivity, then more statistical information is available, but data quality degrades due to scattering, attenuation, and parallax effects at steep axial angles
Solution Approach 1:
The patent applies preliminary anti-action by preemptively filtering out coincidence events with steep axial angles before they can contribute harmful effects to the reconstruction. By calculating and evaluating the axial angle in advance, the system prevents scattering, attenuation, and parallax artifacts from degrading the final image quality
Solution Approach 2:
The patent applies local quality by treating different coincidence events differently based on their specific axial angles. Rather than uniformly processing all data, the system evaluates each event's geometric characteristics and selectively retains only those with favorable angles, ensuring high local quality for each retained event
4Ease of operation
If the radial dimension size is kept fixed for all coincidence data, then data processing is simplified, but valuable information from different radial positions is lost
Solution Approach 1:
The patent introduces dynamics by making the radial dimension size variable rather than fixed. The system dynamically adjusts the radial extent of data retention based on the specific characteristics of each coincidence event, allowing the data structure to adapt to the actual information content rather than forcing all data into a uniform format
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves PET image quality, reduces system cost, data storage needs, and computational burden by retaining only the most valuable coincidence data, thereby enhancing the efficiency of PET imaging systems.
Implementation Method 1
When a positron interacts with an electron by annihilation, the entire mass of the positron-electron pair is converted into two 511 keV photons. The photons are emitted in opposite directions along a line of response.
Implementation Method 2
The annihilation photons (known as (2) singles) are detected by detectors that are placed along the line of response on a detector ring.
Data Source
AI summary
A method and a system for limiting coincidence data includes detecting a plurality of coincidence events during a scan of a subject with a detector array of a positron emission tomography (PET) scanner, wherein the PET scanner includes a plurality of detector rings disposed along a longitudinal axis of the PET scanner, and each detector ring includes a plurality of detectors. The method also includes limiting data associated with the plurality of coincidence events from the scan so that the data varies in a radial extent relative to a center of a field of view of the scan.