Endoscopic laser imaging of tissue perfusion: New instrumentation and technique
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: New instrumentation, based on a previously established laser speckle perfusion imaging (LSI) technique is evaluated for its ability to capture and generate blood flow images during endoscopic surgery. STUDY DESIGN/MATERIALS AND METHODS: Investigations are detailed in an in-vitro blood flow model simulating physiological properties of vascularized tissue, and in-vivo in rabbit joint capsule tissue. RESULTS: In-vitro measurements showed a linear response of the instrument to blood flow in the range of 0-800 microl/minute, where data points were significantly correlated with an r(2) value of 0.96. In-vivo measurements showed a 58.7% decrease to the medial collateral ligament during occlusion of the femoral artery. CONCLUSIONS: Blood flow images demonstrate that the endoscopic LSI technique is capable of measuring relative tissue blood flow changes at high resolutions and rapid response times and incorporates well with endoscopic surgeries.
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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".