Three‐dimensional computed tomographic reconstruction using a C‐arm mounted XRII: Image‐based correction of gantry motion nonidealities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The image quality of 3D reconstructions produced using a C-arm mounted XRII depends on precise determination of the geometric parameters that describe the detector system in the laboratory frame of reference. We have designed a simplified calibration system that depends on images of a metal sphere, acquired during rotation of the gantry through 200 degrees. Angle-dependent shift corrections are obtained, accounting for nonideal motion in two directions: perpendicular to the axis of rotation and tangential to the circular trajectory (tau), and parallel to the axis of rotation (xi). Projection images are corrected prior to reconstruction using a simple shift-interpolation algorithm. We show that the motion of the gantry is highly reproducible during acquisitions within one day (mean standard deviation in tau and xi is 0.11 mm and 0.08 mm, respectively), and over 21 months (mean standard deviation in tau and xi is 0.10 mm and 0.06 mm, respectively). Reconstruction of a small-bead phantom demonstrates uniformity of the correction algorithm over the full volume of the reconstruction [standard deviation of full-width-half-maximum of the beads is approximately 0.25 pixels (0.13 mm) over the volume of reconstruction]. Our approach provides a simple correction technique that can be applied when trajectory deviations are significant relative to the pixel size of the detector but small relative to the detector field of view, and when the fan angle of the acquisition geometry is small (<20 degrees). A comparison with other calibration techniques in the literature is provided.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it