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Record W4223911607 · doi:10.1364/boe.458079

Monte-Carlo simulation and tissue-phantom model for validation of ocular oximetry

2022· article· en· W4223911607 on OpenAlexaff
Cléophace Akitegetse, Patricia Landry, Jonathan Robidoux, Nicolas Lapointe, Danny Brouard, Dominic Sauvageau

Bibliographic record

VenueBiomedical Optics Express · 2022
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImaging phantomMonte Carlo methodFundus (uterus)Computer sciencePulse oximetryRetinalHuman eyeOphthalmologyOpticsMedicineArtificial intelligenceNuclear medicinePhysicsMathematicsStatistics

Abstract

fetched live from OpenAlex

Ocular oximetry, in which blood oxygen saturation is evaluated in retinal tissues, is a promising technique for the prevention, diagnosis and management of many diseases and conditions. However, the development of new tools for evaluating oxygen saturation in the eye fundus has often been limited by the lack of reference tools or techniques for such measurements. In this study, we describe a two-step validation method. The impact of scattering, blood volume fraction and lens yellowing on the oximetry model is investigated using a tissue phantom, while a Monte Carlo model of the light propagation in the eye fundus is used to study the effect of the fundus layered-structure. With this method, we were able to assess the performance of an ocular oximetry technique in the presence of confounding factors and to quantify the impact of the choroidal circulation on the accuracy of the measurements. The presented strategy will be useful to anyone involved in studies based on the eye fundus diffuse reflectance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.358
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2022
Admission routes1
Has abstractyes

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