A Portable Multi-Wavelength near Infrared Photon Time-of-flight Instrument for Measuring Light Scattering
Bibliographic record
Abstract
Measured light scattering properties can be used to improve quantitative spectroscopic analyses of turbid samples. Instruments currently used to measure scattering coefficients are not optimised for portability. A hand-held, dual-wavelength instrument was developed and validated for rapid measurement of reduced scattering coefficients in tandem with near infrared spectra. Tissue simulating phantoms composed of Intralipid and dye were used to model clinically relevant optical properties. Time-dependent intensity profiles of diffusely reflected near infrared pulsed laser light were collected from phantoms and processed to estimate scattering coefficients. In turbid solutions, optical scattering was measured at 850 nm and 905 nm with coefficients of variation of 14.1% and 11.6% over a clinically-relevant reduced scattering coefficient range of 1 mm −1 to 6 mm −1 . This dual-wavelength scattering measurement provides a practical method for measuring optical scattering. A 35% precision improvement in quantification of an absorbing dye is shown by incorporating the measured reduced scattering coefficients when processing NIR spectra. We discuss the new instrument, methods for estimating the scattering coefficient from the measured temporal profiles and, finally, how the reduced scattering coefficient is used to correct NIR measurements. Correction of near infrared spectra using optical scattering measurements offers one direction for improving practical non-invasive biomedical quantification techniques.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".