A Method for accurate in vivo micro-Raman spectroscopic measurements under guidance of advanced microscopy imaging
Bibliographic record
Abstract
The movement from the subjects during in vivo confocal Raman spectral measurements could change the measurement volume, leading to non-specific signals and inaccurate interpretation of the acquired spectrum. Here we introduce a generally applicable method that includes (1) developing a multimodal system to achieve real-time monitoring of every spectral measurement with reflectance confocal microscopy (RCM) and multiphoton microscopy (MPM) imaging; (2) performing region-of-interest measurement by scanning an area of the tissue during spectral acquisition. The developed method has been validated by measuring different micro-structures of in vivo human skin. Our results demonstrated great consistency between RCM images and confocal Raman spectra. The superior quality of the images and spectra allows us to derive blood flow velocity and blood glucose level. We believe this method is valuable for realizing accurate microscopic spectral measurement and have great potential to be adapted into clinic to achieve non-invasive measurement of important biological parameters.
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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".