Image blurring due to light‐sharing in PET block detectors
Bibliographic record
Abstract
The spatial resolution in PET is poorer than that of CT or MRI. All modern PET scanners use block detectors, i.e., clusters of scintillation crystals coupled to four photomultiplier tubes. Some of the loss of spatial resolution in PET is attributed to the use of block detectors, because a photon that interacts with one crystal in the cluster may be incorrectly positioned, resulting in blurring of the reconstructed image. This is called the "block effect." The block effect was measured for detectors from the CTI HR+ scanner, and the GE Advance scanner; two popular clinical PET scanners. The effect of changing the depth of first interaction of a gamma ray in the scintillation crystals was also studied to determine if it may be a contributor to the block effect. The block effect was found to be 1.2 +/- 0.5 mm for the central crystals and negligible for the edge crystals in the CTI HR+ block. It was 0.9 +/- 0.3 mm in the central crystals of the GE Advance detector, and 0.7 +/- 0.3 mm in the edge crystals of the GE Advance detector. In the CTI HR+ detector, a depth dependence on the positioning of the event was observed, as was a dependence on the crystal location (edge versus center). In the GE Advance detector events that occurred at different interaction depths were positioned consistently. The percentage of events that may be positioned inaccurately was also calculated for both detectors. In the CTI HR+ detector as many as 16% of all events in the block detector may be positioned incorrectly. In the GE Advance detector as many as 13% of all events in the block detector may be positioned inaccurately. These results suggest that the depth of interaction of an annihilation photon may contribute to the block effect in detectors that use crystals cut from a single scintillation crystal (pseudodiscrete crystals), and is less dominant a factor for detectors that use discrete crystals with light sharing between the crystals. Investigating the effect of changing photon interaction depth in PET detectors can lead to better detector design, and an intuitive explanation of what sources of blurring may exist in the detector examined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".