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 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 | 0.000 | 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".