Investigation of the sub-pixel spatial resolution and charge-sharing effect in CZT detectors for PET imaging
Bibliographic record
Abstract
1873 Objectives CZT has recently attracted research interests in the development of novel PET imaging[1-5]. However, two challenges need to be addressed to enhance the performances: spatial resolution and charge-sharing effect. The amplitude of transient signal in adjacent pixels can be used to yield sub-pixel spatial resolution. When a photon interacts between two pixels, the charge-sharing effect occurs and both pixels will contribute to output[7,8], which result in charge loss and degrade both charge collection efficiency(CCE) and energy resolution without correction, also the potential to extract the interaction of depth(DOI). Methods The simulation was performed using the Finite Element Method[6]. The output was studied as a function of the pixel pitch and DOI[9].Sub-pixel spatial resolution simulations include the dependence of charges on lateral position and DOI. The electron cloud size is 200um due to diffusion, for pixelated CZT(100um gap), which will cause charge sharing if the interaction is near the pixel edge or between the gap. The charge loss can be presented by CCE. Results Fig.1(c) shows a typical waveform of single pixel event with a noticeable transient signal on the adjacent pixel. 4 group waveforms of left pixel mean 4 DOIs in Fig.1(d), with 10 lateral positions in each group. The amplitude decreases as the interaction from left to right, while the opposite trend is observed for the right pixel. The ratio (Aleft-Aright)/(Aleft+Aright) in Fig.1(e) varies linearly with lateral position and is independent with DOI. In Fig.1(f) the lowest CCE(largset loss) is found to be 0.65 when the interaction occurs between two adjacent pixels. Conclusions Based on the preliminary results, sub-pixel spatial resolution can be achieved using ratio of amplitudes of neighboring pixels. Due to the relatively small amplitude, noise is major limit for the ultimate resolution to be obtained, also the electron cloud size. In addition, a correction for the charge sharing is necessary to improve energy resolution and CCE. Research Support The authors would like to thank Canadian Breast Cancer Foundation Grant (2011R00356), NSERC Engagement Grant (537661), NSERC Discovery Grants, the Canada Research Chair program, and CMC Microsystems for their support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".