Fundamental x-ray interaction limits in diagnostic imaging detectors: Spatial resolution
Bibliographic record
Abstract
The practice of diagnostic x-ray imaging has been transformed with the emergence of digital detector technology. Although digital systems offer many practical advantages over conventional film-based systems, their spatial resolution performance can be a limitation. The authors present a Monte Carlo study to determine fundamental resolution limits caused by x-ray interactions in four converter materials: Amorphous silicon (a-Si), amorphous selenium, cesium iodide, and lead iodide. The "x-ray interaction" modulation transfer function (MTF) was determined for each material and compared in terms of the 50% MTF spatial frequency and Wagner's effective aperture for incident photon energies between 10 and 150 keV and various converter thicknesses. Several conclusions can be drawn from their Monte Carlo study. (i) In low-Z (a-Si) converters, reabsorption of Compton scatter x rays limits spatial resolution with a sharp MTF drop at very low spatial frequencies (< 0.3 cycles/mm), especially above 60 keV; while in high-Z materials, reabsorption of characteristic x rays plays a dominant role, resulting in a mid-frequency (1-5 cycles/mm) MTF drop. (ii) Coherent scatter plays a minor role in the x-ray interaction MTF. (iii) The spread of energy due to secondary electron (e.g., photoelectrons) transport is significant only at very high spatial frequencies. (iv) Unlike the spread of optical light in phosphors, the spread of absorbed energy from x-ray interactions does not significantly degrade spatial resolution as converter thickness is increased. (v) The effective aperture results reported here represent fundamental spatial resolution limits of the materials tested and serve as target benchmarks for the design and development of future digital x-ray detectors.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".