Correction of XRII geometric distortion using a liquid‐filled grid and image subtraction
Bibliographic record
Abstract
X-ray image intensifier (XRII) geometric distortion reduces the accuracy of image-guided procedures and quantitative image reconstructions. Due to the dependence of this error on the earth's magnetic field, the required correction is angle dependent, and calibration data should ideally be acquired simultaneously with clinical image data, at a specific orientation. We describe a technique to correct XRII geometric image distortion at any angular position during a stereotactic procedure. This approach uses a machined plastic grid, which contains channels that can be filled with iodinated contrast agent and subsequently flushed with water, providing contrast and mask images, respectively, of a geometric calibration grid. The standard image subtraction capabilities of conventional digital subtraction angiography devices can then be used to create a subtraction image of the iodine-filled channels, without any confounding anatomical structure. Grid-line intersection points are used to determine the control points that are required for a global polynomial correction algorithm, creating a correction map that is specific to the current angular position and XRII field of view (FOV). Tests with a clinical C-arm based XRII show that control points can be obtained with a precision of +/-0.053 mm, resulting in geometric correction accuracy of +/-0.152 mm, at a nominal FOV of 40 cm. While the precision and accuracy are both poorer than that achieved with a high-contrast steel-bead grid, the fact that the liquid grid can remain rigidly attached to the XRII during an entire procedure results in the establishment of an absolute detector coordinate system (referenced to the liquid-filled correction grid). The design of the liquid-filled channels allows the required control points to be introduced into the image or removed in about 30 s, avoiding the appearance of obscuring or confounding markers during clinical image acquisition, with a concurrent increase in patient dose of about 8% in the current design. Applications for this technique include stereotactic surgery, radiosurgery, x-ray stereogrammetry, and other image-guided procedures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".