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Real-time video-streaming to surgical loupe mounted head-up display for navigated meningioma resection

2017· article· en· W2610756481 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

VenueTurkish Neurosurgery · 2017
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersUniversity of Miami
KeywordsNeuronavigationMedicineOptical head-mounted displayAugmented realityWearable computerImaging phantomComputer visionResectionComputer scienceArtificial intelligenceSurgeryRadiologyEmbedded system

Abstract

fetched live from OpenAlex

Wearable technology interfaces with normal human movement and function, thereby enabling more efficient and adaptable use. We developed a wearable display system for use with intra-operative neuronavigation for brain tumor surgery. The Google glass headup display system was adapted to surgical loupes with a video-streaming integrated hardware and software device for display of the Stealth S7 navigation screen. Phantom trials of surface ventriculostomy were performed. The device was utilized as an alternative display screen during cranial surgery. Image-guided brain tumor resection was accomplished using Google Glass head-up display of Stealth S7 navigation images. Visual display consists of navigation video-streaming over a wireless network. The integrated system developed for video-streaming permits video data display to the operating surgeon without requiring movement of the head away from the operative field. Google Glass head-up display can be used for intra-operative neuronavigation in the setting of intracranial tumor resection.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.611
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 studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.029
GPT teacher head0.325
Teacher spread0.297 · 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