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Enregistrement W3193971877 · doi:10.1016/j.xops.2021.100054

Optimizing Color Performance of the Ngenuity 3-Dimensional Visualization System

2021· article· en· W3193971877 sur OpenAlex

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Notice bibliographique

RevueOphthalmology Science · 2021
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueAdvanced Radiotherapy Techniques
Établissements canadiensUniversity of TorontoSt. Michael's Hospital
Organismes subventionnairesnon disponible
Mots-clésColorimeterColor balanceArtificial intelligenceLuminanceComputer visionMagnificationComputer scienceColor spaceVideographyMathematicsComputer graphics (images)OpticsImage processingColor imagePhysicsArt

Résumé

récupéré en direct d'OpenAlex

PurposeTo evaluate the effect of surgeon-controlled parameters on the color performance of the Ngenuity 3-dimensional (3D) visualization system.DesignA calibrated reference target was placed inside a model eye to assess the Ngenuity 3D camera under different settings. The Ngenuity 3D display was assessed with a commercial colorimeter.MethodsManufacturer-recommended methodology for white balancing was compared against all common deviations in technique. Following white balance, images of a calibrated reference target were extracted and tested using Imatest Master software to calculate quantitative color differences (delta E and delta C). The Ngenuity monitor was assessed using a SpyderX Elite commercial colorimeter to assess for image burn-in by quantifying color uniformity and maximum luminescence.Main Outcome MeasuresDelta E and delta C were calculated for all variables. Color uniformity and luminance were assessed in candelas per square meter (nits).ResultsColor performance using the manufacturer-recommended specifications yielded a delta E of 12.81 ± 1.67. Changing the white balance target to a videography grey card (P = 0.07) and 4 × 4 gauze (P = 0.37) provided similar performance, whereas using white computer paper or the operator’s palm significantly increased the delta E from 12.81 ± 1.67 to 15.28 ± 1.22 (P = 0.01) and 17.71 ± 2.03 (P < 0.01), respectively. Changes to card position, magnification, stability, or ambient lighting did not significantly impact white balance results, whereas having the card in crisp focus did decrease color accuracy (15.78 ± 1.63; P = 0.03). Minor improvement in performance occurred when the laser filter was off for white balance and image acquisition (9.28 ± 0.25; P < 0.01), but deterioration occurred if the laser filter was placed after balancing (16.59 ± 1.17; P < 0.01). Both light sources of 23-gauge light pipe at 34% intensity and 25-gauge chandelier at 50% intensity gave similar color accuracy (P = 0.37). When comparing different Ngenuity machines, color uniformity and maximum luminescence decreased with increased device use.ConclusionsOverall, the Ngenuity 3D has robust color performance. A few limitations of both the camera and monitor were identified, and surgeons should be aware of these pitfalls as well as solutions examined herein to mitigate their effects during surgery. To evaluate the effect of surgeon-controlled parameters on the color performance of the Ngenuity 3-dimensional (3D) visualization system. A calibrated reference target was placed inside a model eye to assess the Ngenuity 3D camera under different settings. The Ngenuity 3D display was assessed with a commercial colorimeter. Manufacturer-recommended methodology for white balancing was compared against all common deviations in technique. Following white balance, images of a calibrated reference target were extracted and tested using Imatest Master software to calculate quantitative color differences (delta E and delta C). The Ngenuity monitor was assessed using a SpyderX Elite commercial colorimeter to assess for image burn-in by quantifying color uniformity and maximum luminescence. Delta E and delta C were calculated for all variables. Color uniformity and luminance were assessed in candelas per square meter (nits). Color performance using the manufacturer-recommended specifications yielded a delta E of 12.81 ± 1.67. Changing the white balance target to a videography grey card (P = 0.07) and 4 × 4 gauze (P = 0.37) provided similar performance, whereas using white computer paper or the operator’s palm significantly increased the delta E from 12.81 ± 1.67 to 15.28 ± 1.22 (P = 0.01) and 17.71 ± 2.03 (P < 0.01), respectively. Changes to card position, magnification, stability, or ambient lighting did not significantly impact white balance results, whereas having the card in crisp focus did decrease color accuracy (15.78 ± 1.63; P = 0.03). Minor improvement in performance occurred when the laser filter was off for white balance and image acquisition (9.28 ± 0.25; P < 0.01), but deterioration occurred if the laser filter was placed after balancing (16.59 ± 1.17; P < 0.01). Both light sources of 23-gauge light pipe at 34% intensity and 25-gauge chandelier at 50% intensity gave similar color accuracy (P = 0.37). When comparing different Ngenuity machines, color uniformity and maximum luminescence decreased with increased device use. Overall, the Ngenuity 3D has robust color performance. A few limitations of both the camera and monitor were identified, and surgeons should be aware of these pitfalls as well as solutions examined herein to mitigate their effects during surgery.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,258
Score d'incertitude au seuil0,203

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,298
Écart entre enseignants0,285 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle