Three‐dimensional reconstruction of limited‐view projections for contrast‐enhanced magnetic resonance angiography at high temporal and spatial resolution
Bibliographic record
Abstract
The feasibility of reconstructing three-dimensional (3D) MRI data sets from limited-view projections is investigated in phantom and in vivo animal studies to improve the temporal resolution of magnetic resonance angiography without sacrificing spatial resolution. Thirty-two pairs of orthogonal biplane projections are acquired in an interleaved manner during the first pass of a contrast agent. The full data set is reconstructed as a priori 3D information. Each pair of projections is then reconstructed into an individual 3D data set based on a correlation analysis with the a priori data set. In this way, time-resolved 3D data sets at 1- to 2-s time intervals are reconstructed with submillimeter spatial resolution. Artifacts are limited if the image is simply structured or sparse and if SNR is sufficient in the projection images. With this technique, both high temporal and spatial resolution can be achieved simultaneously.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".