Numerical optimization for constrained image registration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Image registration or image matching is a technique to establish meaningful correspondences between points in different scenes. It is a mandatory tool for various applications in medicine, geoscience, and other disciplines. However, obtaining plausible deformations is a complex task. For example, many applications require the transformations to be locally invertible, or even harder, keep volume changes within a reasonable bandwidth. In this work, solutions to the registration problem are obtained by direct imposition of a volume constraint on each voxel in a discretized domain. In contrast to previous work, the focus here is on development of an efficient and robust numerical algorithm and in particular, the study of an augmented Lagrangian method with a multigrid solver. The paper demonstrates that this combination yields an almost optimal solver (i.e. linear time) for the problem. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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 it