Motion and deformation compensation for freehand prostate biopsies
Bibliographic record
Abstract
In this paper, we present a registration pipeline to compensate for prostate motion and deformation during targeted freehand prostate biopsies. We perform 2D-3D registration by reconstructing a thin-volume around the real-time 2D ultrasound imaging plane. Constrained Sum of Squared Differences (SSD) and gradient descent optimization are used to rigidly align the moving volume to the fixed thin-volume. Subsequently, B-spline de- formable registration is performed to compensate for remaining non-linear deformations. SSD and zero-bounded Limited memory Broyden Fletcher Goldfarb Shannon (LBFGS) optimizer are used to find the optimum B-spline parameters. Registration results are validated on five prostate biopsy patients. Initial experiments suggest thin- volume-to-volume registration to be more effective than slice-to-volume registration. Also, a minimum consistent 2 mm improvement of Target Registration Error (TRE) is achieved following the deformable registration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".