Deformable registration for intra-operative cone-beam CT guidance of head and neck surgery
Why this work is in the frame
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Bibliographic record
Abstract
The computational and geometric performance of Demons deformable registration techniques were investigated in the application of cone-beam CT (CBCT) for intra-operative guidance of head and neck surgery. A prototype C-arm providing CBCT images of sub-mm spatial resolution and soft-tissue contrast was used to acquire images of a cadaveric head before and after surgical intervention. Four deformable registration methods were investigated both in terms of their convergence behavior (time and number of iterations required) and registration accuracy (correlation between deformed and target images and the corresponding target registration error, TRE). Rigid registration alone exhibited a TRE of (2.6 +/- 1.0) mm, compared to a TRE of (0.8 +/- 0.3) mm obtained with deformable registration. A fast symmetric demons implementation was identified as the most suitable for intra-operative use in terms of speed, image quality, and accuracy. Increasing the spatial resolution of CBCT images was found to increase registration accuracy at the cost of computational expense. Intra-operative CBCT combined with deformable registration offers to overcome conventional limitations of guidance by preoperative images alone and presents an accurate method of integrating imaging and planning data in a manner that properly reflects changes in the intra-operative state.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it