Design and development of a rotating-anode x-ray tube coherent scatter projection imaging system
Bibliographic record
Abstract
Coherent x-ray scatter is material specific, and imaging systems utilizing information from coherently scattered x rays are promising for security and medical applications requiring material identification with high sensitivity. A persistent challenge for practical implementation of these systems has been slow image acquisition. Our approach to reducing acquisition time is to develop a multibeam projection imaging system rather than a volumetric (CT or otherwise) imaging system. Previously we implemented a synchrotron-based system with five coplanar pencil beams and continuous motion of the object. Now we present a tabletop x-ray scatter imaging system built using a rotating-anode x-ray tube and a scintillating, energy-integrating flat-panel detector. A conventional source is more challenging to use than a synchrotron beam due to polychromaticity, low intensity, beam divergence, and x-ray tube thermal considerations. Simulations were performed to determine the system layout that optimized the intensity and angular resolution of scatter signals. The tube is inclined 6.1° to reduce apparent focal spot size. The primary collimation allows for an array of up to three rows by five columns of pencil beams, 3mm diameter and 2 cm apart at the object midplane 35 cm from the source, to irradiate the object simultaneously. There is no scatter collimation and the multiplexed scatter signals are disentangled using a maximum-likelihood expectation maximization algorithm. Motorized translation stages scan the object through the beams. The system can image objects up to 10 × 10 × 10 cm<sup>3</sup> and 1 kg. Post-object primary beam attenuators allow for the same detector to measure transmitted and scattered x rays simultaneously. Initial images acquired with the system are presented. Using 15 beams, a 6000-pixel scatter image of a 6 cm × 10 cm region was acquired in 4.6 min.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".