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Record W2121348084 · doi:10.1109/imtc.2005.1604081

Retinal Motion and Microvascular Pulsation Measurements from SLO Image Sequences

2006· article· en· W2121348084 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venue2005 IEEE Instrumentationand Measurement Technology Conference Proceedings · 2006
Typearticle
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsCarleton University
FundersCanadian Space Agency
KeywordsComputer visionArtificial intelligenceComputer scienceMotion estimationSaccadic maskingImage resolutionOpticsAdaptive opticsLaserEye movementPhysics

Abstract

fetched live from OpenAlex

Scanning laser ophthalmoscopes (SLOs) provide noninvasive image sequences of the retina with high temporal and spatial resolution. This paper describes recent methods and results for accurate saccade and drift motion estimation of the eye. The proposed method exploits the scanning nature of the SLO and assumes direct access to each scan line as it is received. This approach allows high temporal resolution in estimation of saccadic motion that is used in prediction of landmark motion for extraction of translational and rotational estimates due to drift. The high accuracy achieved leads to the capability to track specific vascular structures of interest during the image sequence. We demonstrate applications in measurement of the amplitude of the venous pulse, often observed in vessels at or near the edge of the optical disk, relative to distance along the vessel. Results are shown for both simulated and real SLO image sequences

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.257
Teacher spread0.227 · 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