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Record W1587066005 · doi:10.1109/iembs.2003.1279797

Projector-based augmented reality in surgery without calibration

2004· article· en· W1587066005 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsPolytechnique MontréalUniversité de Montréal
Fundersnot available
KeywordsProjectorAugmented realityComputer scienceComputer visionArtificial intelligencePixelCalibrationOptical head-mounted displayComputer graphics (images)SimplicityMathematics

Abstract

fetched live from OpenAlex

Augmented reality (AR) is becoming an important tool in surgery to support the surgeon and improve operation quality, safety and duration. However the AR setup with head-mounted display (HMD) and other equipments is often considered cumbersome by surgeons and limits its wide use in the operating room. To reduce this burden, we introduce a new approach to display undistorted image data directly on the patient (skin, bone, surgery linen etc.) without explicit camera and projector calibration. With a single camera used to capture the surgeon's field of view, the calibration is implicitly represented as a mapping establishing the correspondence of each pixel of a camera to a pixel from a projector. After this mapping has been carried out, one can display an image corrected for the surgeon. Results are presented showing the simplicity and potential of the method for an operating room.

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)0.000
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 score0.957
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.045
GPT teacher head0.289
Teacher spread0.245 · 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

Quick stats

Citations21
Published2004
Admission routes1
Has abstractyes

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