Next generation high resolution perovskite direct conversion detector: Monte Carlo design optimisation and virtual clinical trial
Bibliographic record
Abstract
We implement virtual clinical integration of next-generation perovskite detectors into common x-ray imaging devices. This was achieved by performing Monte Carlo (MC) optimisation of the design and benchmarking of low cost, high spatial resolution, direct conversion perovskite crystal x-ray flat panel imagers for a next generation of breast-, MV-, and kV-cone beam CT detectors. Semiconductor methylammonium lead bromide perovskite crystals energy deposition efficiencies calculated in TOPAS were benchmarked against four common detector materials for twelve detector crystal thicknesses between 40 to 15 mm and ten beam energies ranging from 20 keV to 6 MeV. Based on these simulations, Koning's dedicated breast CT, and Varian's Truebeam kV- and MV-cone beam CT systems were designated as suitable applications for perovskite detectors. System specific Fastcat hybrid MC cone beam CT image simulation was subsequently used to optimise the perovskite detector design and conduct virtual clinical trials. Device-specific optimal perovskite crystal thicknesses were calculated to be 0.30, 0.86, and 1.99 mm for Koning breast CT and Truebeam kV- and MV-cone beam CT systems, respectively. Replacing the current detectors on these machines with low cost perovskite crystal detectors could be advantageous as it would simultaneously yield 12.1%, 9.5% and 86.1% improvements in detective quantum efficiency as well as increases in contrast to noise ratio in brain, lung, and bone tissues.
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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 | 0.001 | 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".