Performance evaluation of small pixel-sized Gd2O2S and CsI CMOS x-ray detectors
Bibliographic record
Abstract
Flat panel x-ray detectors with thin-film transistors (TFT) are widely used in x-ray medical imaging applications. However, indirect x-ray detectors with TFT suffer from an inadequate spatial resolution that is required for some medical imaging procedures, where resolving fine details at its early stage plays a crucial role in successful diagnosis such as breast imaging. Besides, indirect conversion x-ray detectors when incorporated with common types of scintillators, i.e., cesium iodide (CsI) or Gd2O2S, can meet the requirements of high fabrication yield and respectively lower costs. As an alternative to TFT read-out circuitry, complementary metal oxide semiconductor (CMOS) presents an attractive alternative, offering lower inherent electrical noise and higher temporal resolution, enabling dynamic imaging at lower x-ray doses. The purpose of this work is to develop small pixel size indirect conversion CMOS x-ray detectors. The CsI-based detector features an active area of 1.1x0.8cm2 and a pixel size of 20μm, while the Gd2O2S-based detector has an active area of 1.5x1.5cm2 and a pixel size of 20μm. Both detectors comprise of 1024x1024 pixels with an image depth of 14 bits. However, the active area of the CsI-based detector is less than that of the Gd2O2S-based detector. To evaluate the spatial resolution of the detectors, the IEC 62220-1:2003 standard is followed. The modulation transfer function (MTF) of both detectors is examined experimentally by the slanted-edge method using the first two prototype CMOS detectors. The initial results indicate that the point at which the MTF reaches 50% is significantly higher for both indirect CMOS detectors compared to commercial CMOS and TFT detectors utilizing the same scintillators. Specifically, the Gd2O2S-based detector achieves 2.6lp/mm, while the CsI-based detector reaches 4.7lp/mm. Also, the preliminary images of the medical stent used for angiography operation obtained with the fabricated detectors demonstrate that the indirect conversion CMOS x-ray detectors can be a reasonable alternative to direct conversion x-ray detectors for some specific imaging operations. In addition to MTF, noise power spectrum (NPS), and detective quantum efficiency (DQE) values are also examined. This study is the first attempt to explore our indirect CMOS x-ray detectors and further studies will be carried out to identify their potential application area in medical imaging procedures.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".