Dual-beam manually-actuated catheters for wide-field distortion-corrected optical imaging
Bibliographic record
Abstract
Previously, we have demonstrated two fiber optic catheter implementations of dual-beam manually-actuated distortion-corrected imaging (DMDI) that employ rotationally-scanning micromotors that are potentially suitable for endoscopic imaging applications. These catheters are able to correct for both axial (push/pull) and azimuthal (catheter rotation) manual actuation. We presented a multiplexed dual beam micromotor catheter (mDBMC), an OCT-specific design that depth-multiplexes both imaging channels within a single optical fiber and a dual-fiber parallel DBMC (pDBMC) design that is suitable for any point-scanning modality such as OCT, fluorescence, or reflectance imaging. As the mDBMC has a relatively simple scan pattern, we developed a straightforward automated method for distortion correction based on image frame cross-correlation. Due to the complicated scan pattern of the pDBMC, we initially co-registered image features for the pDMBC in a time-consuming manual process. In this work, we describe our efforts to develop an automated distortion correction method for the pDMBC. We demonstrate initial success in automated correction along the pullback dimension.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".