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Long axial FOV data bring new imaging opportunities and potential of improved reconstruction quality, but also challenges caused by dramatic increase of data sizes and challenges given by the change and variations of data characteristics with increased acceptance angles.
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Good TOF resolution and considerably increased sensitivity of total-body imaging scanners allow novel and improved modeling and ways of processing their data.
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Total-body PET enables simultaneous dynamic imaging of the entire
3D/4D Reconstruction and Quantitative Total Body Imaging
Section snippets
Key points
Basics
Total-body PET scanners have a huge number of lines of response (LORs). For example, the uEXPLORER scanner (United Imaging Healthcare, Shanghai, China) has more than half a million individual crystals, forming more than 90 billion LORs.1,2 With time-of-flight (TOF) information, the number of elements in a TOF sinogram is more than 1 trillion, which is far greater than the number of coincidence events that could be detected in a regular scan. For example, a 1-hour dynamic scan following a 256
Efficient reconstruction using direct image reconstruction for time-of-flight data framework
Although list-mode reconstruction has the advantage of facilitating straightforward and accurate modeling (in forward projection) for each acquired event, this is at the cost of having to separately calculate forward- and back-projection operations for each individual event, leading to high computational demands. Direct image reconstruction for TOF data (DIRECT)22 represents an alternative, efficient, reconstruction approach taking advantage of the considerably decreased angular sampling
Frame-by-Frame Reconstruction Using the Kernel Method
In the setting of dynamic PET imaging, the expectation of the LOR measurement in the time frame is described byfor with the total number of time frames.a Similar to the kernel method for standard dynamic
Summary and future prospects
Total-body PET provides challenges and opportunities for 3D/4D PET image reconstruction. On the one hand, the large dataset size presents a daunting challenge in computation. Incorporation of the long oblique LORs in reconstruction also requires an accurate model of the response function and proper handling of the correction factors, such as normalization and scatter correction. On the other hand, the high photon-detection sensitivity of total-body PET provides sufficient count density to take
Acknowledgments
Dr J. Qi reports support by grants from the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and the National Cancer Institute (NCI) of the National Institutes of Health (NIH) under Award Nos. R01EB000194, R21EB026668, R01CA206187 and funding through a sponsored research agreement by Canon Medical Research USA. Dr G. Wang reports support by grants from NCI and NIBIB under Award Nos. K12 CA138464, R01CA206187, P30CA093373, and R21 EB027346. Dr S. Matej reports support by
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