3D fluoroscopy with real‐time 3D non‐cartesian phased‐array contrast‐enhanced MRA
Bibliographic record
Abstract
For optimized CE-MRA of the chest and abdomen, the scan time and breath-hold must be coordinated with the arrival of contrast. A 3D fluoroscopy system is demonstrated that performs real-time 3D projection reconstruction acquisition, reconstruction, and visualization using only the standard scanner hardware and operator console workstation. Unlike 2D fluorotriggering techniques, no specification of a monitoring slab or careful placement of the imaging volume is required. 3DPR data are acquired continuously throughout the examination using an eight-channel receiver and 1 s interleaved subframes. The data are reconstructed using 1 s segments for real-time monitoring with 0.8-cm isotropic spatial resolution over the entire torso, allowing full-volume axial, coronal, and sagittal MIPs to be displayed simultaneously with minimal latency. The system later uses the same scan data to generate high-spatial-resolution time-resolved sequences of the breath-hold interval. The 3D fluoroscopy system was validated on phantoms and human volunteers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".