Design and implementation of a 3D-MR/CT geometric image distortion phantom/analysis system for stereotactic radiosurgery
Bibliographic record
Abstract
Abstract The design, construction and application of a multimodality, 3D magnetic resonance/computed tomography (MR/CT) image distortion phantom and analysis system for stereotactic radiosurgery (SRS) is presented. The phantom is characterized by (1) a 1 × 1 × 1 (cm) 3 MRI/CT-visible 3D-Cartesian grid; (2) 2002 grid vertices that are 3D-intersections of MR-/CT-visible ‘lines’ in all three orthogonal planes; (3) a 3D-grid that is MR-signal positive/CT-signal negative; (4) a vertex distribution sufficiently ‘dense’ to characterize geometrical parameters properly, and (5) a grid/vertex resolution consistent with SRS localization accuracy. When positioned correctly, successive 3D-vertex planes along any orthogonal axis of the phantom appear as 1 × 1 (cm) 2 -2D grids, whereas between vertex planes, images are defined by 1 × 1 (cm) 2 -2D arrays of signal points. Image distortion is evaluated using a centroid algorithm that automatically identifies the center of each 3D-intersection and then calculates the deviations d x , d y , d z and d r for each vertex point; the results are presented as a color-coded 2D or 3D distribution of deviations. The phantom components and 3D-grid are machined to sub-millimeter accuracy, making the device uniquely suited to SRS applications; as such, we present it here in a form adapted for use with a Leksell stereotactic frame. Imaging reproducibility was assessed via repeated phantom imaging across ten back-to-back scans; 80%–90% of the differences in vertex deviations d x , d y , d z and d r between successive 3 T MRI scans were found to be ⩽0.05 mm for both axial and coronal acquisitions, and over >95% of the differences were observed to be ⩽0.05 mm for repeated CT scans, clearly demonstrating excellent reproducibility. Applications of the 3D-phantom/analysis system are presented, using a 32-month time-course assessment of image distortion/gradient stability and statistical control chart for 1.5 T and 3 T GE Twin Speed MRI systems.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".