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Record W2289996177

ACCURACY OF ELECTROMAGNETIC TRACKING IN AN IMAGE-GUIDED SURGERY SUITE

2018· article· en· W2289996177 on OpenAlexaboutno aff
Elodie Lugez, David R. Pichora, Selim G. Akl, R.E. Ellis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
Fundersnot available
KeywordsOrientation (vector space)FluoroscopyPosition (finance)Tracking (education)Computer scienceInterference (communication)OpticsNoise (video)Electromagnetic interferenceAcousticsPhysicsComputer visionArtificial intelligenceMathematicsTelecommunicationsGeometry
DOInot available

Abstract

fetched live from OpenAlex

Recently, electromagnetic tracking for surgical procedures has gained popularity due to its small sensor size and the absence of line-of-sight restrictions. However, EM trackers are susceptible to measurement noise. Indeed, depending on the environment, measurement uncertainties may vary considerably. Therefore, it is important to characterise electromagnetic measurement systems when used in a fluoroscopy setting. The purpose of our study is to assess decoupled static electromagnetic measurement errors in position and orientation, without adding potential interference, in the presence of fluoroscopic imaging equipment. Using an Aurora electromagnetic tracking system (Northern Digital, Waterloo, Canada), 5 degrees of freedom measurements were collected in a working space located midway between the source and the receiver of a flat-panel 3D fluoroscope (Innova 4100, GE Healthcare, Buc, France) emitting X-rays. In addition, to determine potential EM distortion from X-rays, electromagnetic measurement accuracies, as a function of position, were compared before, during, and after X-ray emissions. To decouple position and orientation errors, two scaffold devices were designed. Their centre was placed approximately at X = −50, Y = 0, and Z = −300 mm in the EM tracker9s global coordinate system. First the positioning scaffold was used to assess the position and orientation measurement uncertainties as a function of position. Next, the orienting scaffold was used to assess the position and orientation measurement uncertainties as a function of orientation. Then, a least-squares method was employed to register the path position measurements to the known geometry of the scaffolds. As a result, the position accuracy was defined as the Euclidean distance between the registered and the ground truth positions. Finally, the orientation accuracy was defined as the difference between two direct angles: the angle between two measured consecutive paths, and the angle of the corresponding ground truth. When translating the sensor using the positioning scaffold, the resulting position accuracy was characterised by a mean of 3.2 mm. Similarly, when rotating the sensor using the orienting scaffold, the resulting orientation accuracy was characterised by a mean of 1.7 deg. As for the “cross-displacement” errors, the orientation accuracy as a function of position had a mean of 1.8 deg. Likewise, the position as a function of orientation had a mean of 4.0 mm. Position and orientation accuracies – as a function of position, before, during, and after emission of X-rays – indicate that there was no significant interference by the presence of an X-ray beam on the EM measurements. This work provides evidence that placing the EM system into X-ray beams does not affect EM measurement accuracies. Nevertheless, the fluoroscope itself significantly increases the EM measurement errors. Careful analysis of the EM measurement distribution errors suggests that associated uncertainties are predictable and preventable. In essence, EM tracking is promising for orthopedic procedures that may require the use of a fluoroscope.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.309
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2018
Admission routes1
Has abstractyes

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