Analytical Models of Optical Coherence Tomography for Tissue Optical Property Estimation: Preliminary Result and Comparison
Bibliographic record
Abstract
Optical Coherence Tomography (OCT) can provide non-invasive imaging of living tissues based on the principle of optical interferometry. Though there is an abundant amount of literature on OCT image processing and segmentation, recovering optical parameters of the biological tissue from OCT data remains a challenge and demands further research, as tissue optical properties play an important role in disease diagnosis. In this paper we consider estimating tissue optical properties from OCT data as an inverse problem. We will review the main approaches for the forward step of the inverse problem to generate the OCT signal using both the extended Huygens-Fresnel principle (EHF), which is a theoretical model for OCT imaging based on optics, and the Radiative Transfer Equation (RTE), which describes mathematically the energy transfer through a media. Our experimental results show a clear agreement between these two models for OCT modelling.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".