Poster — Wed Eve—13: Evaluation of Spectroscopic Compton Tomography Approach at 55 keV
Bibliographic record
Abstract
The feasibility of reconstructing 2D electron density ( ) images has been studied. The spectroscopic measurement of Compton scattered photons in a single projection computed tomography (CT) fan beam geometry at 55 keV was investigated. Images were reconstructed by backprojecting over circular paths. A line of energy sensitive detectors was placed outside of periphery of the primary x‐ray fan beam to record the number of scattered photons. The forward problem was simulated in Matlab using analytical equations containing the Klein‐Nishina scattering cross sections, electron density of the object and the solid angle between the point of scattering and the detector. A narrow energy spectrum was needed to achieve good resolution. As the FWHM of the incident spectrum increases, the location where the scatterer can be detected with high precision, decreases. The spatial resolution varies across the image and areas of higher spatial resolution are those which exhibit small angle scattering to the detectors close to the source. Thus various target/filter combinations were studied. The optimal spectrum can be generated by an x‐ray tube operated at 90 kVp with a tungsten target and filter consisting of 0.5mm tungsten and 1.2mm erbium. A point source and ideal detectors were used and no multiple scatter or attenuation was considered. Electron densities were reconstructed using this approach for two phantoms and good qualitative results were obtained. Our ultimate goal is to produce 3D images from scattered photons in a multi‐projection cone‐beam breast CT geometry.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".