A truly hybrid interventional MR/X-ray system: Feasibility demonstration
Bibliographic record
Abstract
A system enabling both x-ray fluoroscopy and MRI in a single exam, without requiring patient repositioning, would be a powerful tool for image-guided interventions. We studied the technical issues related to acquisition of x-ray images inside an open MRI system (GE Signa SP). The system includes a flat-panel x-ray detector (GE Medical Systems) placed under the patient bed, a fixed-anode x-ray tube overhead with the anode-cathode axis aligned with the main magnetic field and a high-frequency x-ray generator (Lunar Corp.). New challenges investigated related to: 1) deflection and defocusing of the electron beam of the x-ray tube; 2) proper functioning of the flat panel; 3) effects on B0 field homogeneity; and 4) additional RF noise in the MR images. We have acquired high-quality x-ray and MR images without repositioning the object using our hybrid system, which demonstrates the feasibility of this new configuration. Further work is required to ensure that the highest possible image quality is achieved with both MR and x-ray modalities.
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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 | 0.001 |
| 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".