Comparative study of differential matrix and extended polar decomposition formalisms for polarimetric characterization of complex tissue-like turbid media
Why this work is in the frame
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Bibliographic record
Abstract
Development of methodologies for quantification/unique interpretation of the intrinsic polarimetry characteristics of biological tissues are important for various applications involving tissue characterization/diagnosis. A detailed comparative evaluation of the polar decomposition and the differential matrix decomposition of Mueller matrices for extraction/quantification of the intrinsic polarimetry characteristics (with special emphasis on linear retardance δ, optical rotation Ψ and depolarization Δ parameters was performed, because these are the most prominent tissue polarimetry effects) from complex tissue-like turbid media exhibiting simultaneous scattering and polarization effects. The results suggest that for media exhibiting simultaneous linear retardance and optical rotation polarization events, the use of retarder polar decomposition with its associated analysis which assumes sequential occurrence of these effects, results in systematic underestimation of δ and overestimation of Ψ parameters. Analytical relationships between the polarization parameters (δ, Ψ) extracted from both the retarder polar decomposition and the differential matrix decomposition for either simultaneous or sequential occurrence of the linear retardance and optical rotation effects were derived. The self-consistency of both decompositions is validated on experimental Mueller matrices recorded from tissue-simulating phantoms (whose polarization properties are controlled, known a-priori, and exhibited simultaneously) of increasing biological complexity. Additional theoretical validation tests were performed on Monte Carlo-generated Mueller matrices from analogous turbid media exhibiting simultaneous depolarization (Δ), linear retardance (δ) and optical rotation (Ψ) effects. After successful evaluation, the potential advantage of the differential matrix decomposition over the polar decomposition formalism was explored for monitoring of myocardial tissue regeneration following stem cell therapy.
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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 it