A transmissive laser speckle imaging technique for measuring deep tissue blood flow: An example application in finger joints
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Laser speckle perfusion imaging (LSPI) is a minimally invasive optical measure of relative changes in blood flow, providing real-time, high resolution, two-dimensional maps of vascular structure. Standard LSI imaging uses a light-reflective geometry that limits the measurement to a thin surface layer of 0.2-1 mm. The objective of this study was to test a new LSI instrument geometry with the laser source opposed to the image capture plane (light transmissive). Captured light then travels the entire tissue thickness (10-15 mm), sampling much deeper regions of interest than conventional optical imaging techniques. STUDY DESIGN: Reflective-light (conventional) and transmissive-light LSI modes were used to measure finger joint blood flow during a timed tourniquet occlusion of the brachial artery in volunteer participants. RESULTS: There was greatly increased visibility of vessels underlying the skin in the light-transmissive mode LSI mode. Established LSI algorithms were shown to still work in the light-transmissive mode, despite decorrelation due to finite laser coherence length and the light passing through a tissue thickness of 10-15 mm. CONCLUSION: Transmissive LSI can be used to measure blood flow deep (10-15 mm) into tissues. This could be useful for non-invasive measurements of finger joint synovial blood flow in diagnosing and treating peripheral vascular disorders, such as rheumatoid arthritis.
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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 | 0.001 | 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".