Performance of a static‐anode/flat‐panel x‐ray fluoroscopy system in a diagnostic strength magnetic field: A truly hybrid x‐ray/MR imaging system
Bibliographic record
Abstract
Minimally invasive procedures are increasing in variety and frequency, facilitated by advances in imaging technology. Our hybrid imaging system (GE Apollo flat panel, custom Brand x-ray static anode x-ray tube, GE Lunar high-frequency power supply and 0.5 T Signa SP) provides both x-ray and MR imaging capability to guide complex procedures without requiring motion of the patient between two distant gantries. The performance of the x-ray tube in this closely integrated system was evaluated by modeling and measuring both the response of the filament to an externally applied field and the behavior of the electron beam for field strengths and geometries of interest. The performance of the detector was assessed by measuring the slanted-edge modulation transfer function (MTF) and when placed at zero field and at 0.5 T. Measured resonant frequencies of filaments can be approximated using a modified vibrating beam model, and were at frequencies well below the 25 kHz frequency of our generator for our filament geometry. The amplitude of vibration was not sufficient to cause shorting of the filament during operation within the magnetic field. A simple model of electrons in uniform electric and magnetic fields can be used to estimate the deflection of the electron beam on the anode for the fields of interest between 0.2 and 0.5 T. The MTF measured at the detector and the DQE showed no significant difference inside and outside of the magnetic field. With the proper modifications, an x-ray system can be fully integrated with a MR system, with minimal loss of image quality. Any x-ray tube can be assessed for compatibility when placed at a particular location within the field using the models. We have also concluded that a-Si electronics are robust against magnetic fields. Detailed knowledge of the x-ray system installation is required to provide estimates of system operation.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".