Speckle noise reduction in coherent spatial frequency domain imaging
Bibliographic record
Abstract
This work applies spatial frequency domain imaging (SFDI) to extract optical absorption and reduced scattering values (μa and μs’) of tissue-like samples, with a coherent light source. Here, we evaluate SFDI illuminated by a multi-wavelength vertical-cavity-surface-emitting-laser (VCSEL) array, with selectable wavelengths of 680nm, 795nm and 850nm. The speckle noise is mitigated with a rapid current sweep and with the overlapping of up to three diode lasers per wavelength. The current sweep spans over the single- and multi- transverse mode regimes, to achieve a shorter coherence length and therefore reduce speckle-related noise. Results show a more accurate measurement for the reduced scattering than the absorption coefficient (average error of 1.8% and 11.5% respectively, with 850nm diodes) on tissue phantoms, with the current sweep applied, which is comparable to an incoherent LED source (4.4% and 13.6%). Further reduction in speckle-related noise is observed by illuminating with multiple diodes of the same wavelength. At 850nm, illumination with three diodes causes a noise of 11.5±3.3% in absorption measurements, which is lower than the noise when using a single diode (14.9±4.3%).
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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".