SU‐E‐J‐20: Evaluation of Image Qualities and Registration of Varian KV‐CBCT Images Reconstructed from the Reduced Number of Projections
Bibliographic record
Abstract
PURPOSE: To quantitatively investigate image qualities of the kilo-voltage cone-beam CT images reconstructed with reduced number of projections on the Varian OBI system. Evaluate the registration accuracy using those CBCT images against the reference CT images. METHODS: CBCT images were obtained from Varian OBI system using standard dose head, pelvis and pelvis spotlight modes. CBCT reconstructions were performed with full, 1/2, 1/4, 1/6 and 1/8 of the full set of projections. Catphan® 504 phantom was used to evaluate high-contrast spatial resolution, low-contrast visibility and uniformity. Rando phantom was imaged for rigid registration study. Rando was set up on the linac couch deliberately shifted by 1cm in vertical, lateral, and longitudinal (no rotational) directions from the reference position. Automatch followed by manual adjustment was conducted 5 times to obtain the average shifts. The same method of analysis in the Rando study was used for the clinical registration study. One patient was imaged with pelvis mode and two patients were imaged with pelvis spotlight mode. RESULTS: The Catphan study indicates that high-contrast spatial resolution and uniformity are virtually not affected by the lowest projection-number (1/8) reconstruction scheme. However low-contrast visibility degrades when the projection number used for reconstruction is as low as 1/6. Rando study shows that registration accuracy can be achieved with images reconstructed with 1/6 of the full set of projections. Patient study shows similar results exhibited in Rando study. However, noisy images and streak artifacts are more pronounced with fewer projections (approximate 1/6), which decreases viewer's ability to visualize soft tissues in pelvic sites. CONCLUSIONS: This study shows that KV-CBCT reconstructed with fewer number (approximately as low as 1/6) of regular projections can be used for registration against the reference CT. Although the results are encouraging, more clinical cases should be evaluated in the future. None.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".