USING SINGLES DATA TO RAPIDLY GENERATE GEOMETRIC CORRECTION FOR PET DATA RECONSTRUCTION
Publication Date: 2016-Sep-27
The IP.com Prior Art Database
A technique for using singles data to rapidly generate geometric correction for positron emission tomography (PET) data reconstruction is proposed. The technique involves using singles data from each detector and knowledge of position of source to generate raw values in each geometrical correction sinogram bin. Since singles are acquired at much higher rates than coincidences, the total acquisition time is much shorter. The technique may be varied by using geometric symmetries to further reduce statistical noise, having the source be either a point source or a line source which is rotated around the scanner, identifying the source location in the PET field-of-view by either the mechanical positioning device and/or from coincidence data, and moving the source in a continuously rotating manner or in a step-and-shoot fashion.
The present disclosure relates generally to positron emission tomography (PET) data reconstruction and more particularly to a technique for using singles data to generate geometric correction.
Generally, during positron emission tomography (PET) reconstruction, a normalization correction (norm) is applied to the data which compensates for the unequal sensitivity of each line-of-response (LOR). The norm is a product of a detector efficiency component and a geometric sensitivity component. The geometric sensitivity component is a geometric correction (geocorr). The first step for generating a geocorr array is to acquire data using a mechanical apparatus, such as a T-ring setup depicted in Figure 1. The T-ring setup acquires coincidence data from a line source. To keep statistical noise low, the acquisition requires an extremely large number of events. Further, since the source strength is required to be low to reduce dead time and pileup artifacts, the acquisition takes several days to gather the requisite number of events.
The raw coincidence sinogram acquired is processed using an algorithm, such as the algorithm depicted in Figure 2, to produce the geocorr. Many variations of this algorithm may be used. For example, the order of applying the corrections and symmetries may be varied, or additional correction terms may be applied depending on the specifics of the scanner geometry. However, all variations of the algorithm will start with coincident data files.
Since the normalization correction is related to the geometric correction via the crystal efficiencies 𝑁𝑖j=𝜀𝑖𝜀𝑗 𝑔𝑖j and singles are commonly used to get the crystal efficiencies, singles have been claimed to be used to obtain normalization in some alternative conventional techniques. However, conventional techniques do not use singles data to determine the geometric correction portion.
It would be desirable to have a technique for using singles data to rapidly generate geometric correction for PET data reconstruction.
BRIEF DESCRIPTION OF DRAWINGS
Figure 1 depicts a T-Ring mechanical setup for generating a geocorr array by acquiring coincidence data from a line source.
Figure 2 depicts an algorithm for processing raw coincidence sinogram acquired to produce the geocorr.
Figure 3 depicts definition of Line-of-Response (LOR) coordinates using (s, φ, v, θ).
Figure 4 depicts a 3D angle of incidence as Γ, 2D projection angles Φ and Θ onto the transaxial and axial planes and a perpendicular vector for a single crystal being struck by a photon (γ) for singles interactions according to the proposed technique.
Figure 5 known location and orientation of the detector and known location of a source.
Figure 6 depicts axial and transaxial directions of photon for simplest version of compensation factor F.
Figure 7 depicts relationship between source position and angle-of-incid...