Matches in SemOpenAlex for { <https://semopenalex.org/work/W2995704479> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W2995704479 abstract "Abstract Retinal oximetry is a non‐invasive imaging technology that enables the measurement of oxygen saturation (StO 2 ) in the eye fundus. The goal of this research was to validate a convolutional neural network (CNN) algorithm designed to calculate and improve the precision of StO 2 measurements from diffuse reflectance spectra (DRS) taken on the optic nerve head (ONH). Zilia’s multi‐wavelength retinal oximetry device was used to acquire experimental spectra from the ONH which allowed us to simulate reasonable digital spectra replicates with known absorber concentrations. These spectra were used to train a novel machine learning algorithm based on CNN. The device was then used to acquire diffuse reflectance spectra on several ONH‐mimicking liquid optical phantoms (phantom eye) with dynamic oxygenation cycles between 0% ‐ 100% in order to validate the improvements of this CNN on experimental data. Measurements were made simultaneously with gold standard devices for comparison. The procedure was then repeated with several cataract‐simulating contact lenses integrated in the optical path to show the robustness of oximetry measurements. We found good agreement in StO 2 measurements between the results obtained with the Zilia device using the CNN algorithm and the gold standard references in all phantom cases. Applying the various algorithms to data acquired on the validation phantom show the marked improvements in using the CNN on experimental data, validating its high potential for clinical use. We specifically show strong robustness in precision, even when cataract‐simulating lenses were used. We present further validation that the oximetry device and CNN algorithm produces reliable, precise measurements even under conditions where blood volume fractions vary, optical scattering changes, and cataract‐simulating contact lenses are included." @default.
- W2995704479 created "2019-12-26" @default.
- W2995704479 creator A5026950029 @default.
- W2995704479 creator A5031712808 @default.
- W2995704479 creator A5037753193 @default.
- W2995704479 creator A5041516672 @default.
- W2995704479 creator A5062265776 @default.
- W2995704479 creator A5073291285 @default.
- W2995704479 creator A5082444978 @default.
- W2995704479 creator A5091069380 @default.
- W2995704479 date "2019-12-01" @default.
- W2995704479 modified "2023-10-17" @default.
- W2995704479 title "Improvement and validation of high precision ocular oximetry using a convolutional neural network algorithm and a phantom eye" @default.
- W2995704479 doi "https://doi.org/10.1111/j.1755-3768.2019.5463" @default.
- W2995704479 hasPublicationYear "2019" @default.
- W2995704479 type Work @default.
- W2995704479 sameAs 2995704479 @default.
- W2995704479 citedByCount "0" @default.
- W2995704479 crossrefType "journal-article" @default.
- W2995704479 hasAuthorship W2995704479A5026950029 @default.
- W2995704479 hasAuthorship W2995704479A5031712808 @default.
- W2995704479 hasAuthorship W2995704479A5037753193 @default.
- W2995704479 hasAuthorship W2995704479A5041516672 @default.
- W2995704479 hasAuthorship W2995704479A5062265776 @default.
- W2995704479 hasAuthorship W2995704479A5073291285 @default.
- W2995704479 hasAuthorship W2995704479A5082444978 @default.
- W2995704479 hasAuthorship W2995704479A5091069380 @default.
- W2995704479 hasConcept C104293457 @default.
- W2995704479 hasConcept C104317684 @default.
- W2995704479 hasConcept C11413529 @default.
- W2995704479 hasConcept C120665830 @default.
- W2995704479 hasConcept C121332964 @default.
- W2995704479 hasConcept C154945302 @default.
- W2995704479 hasConcept C185592680 @default.
- W2995704479 hasConcept C31972630 @default.
- W2995704479 hasConcept C41008148 @default.
- W2995704479 hasConcept C55493867 @default.
- W2995704479 hasConcept C63479239 @default.
- W2995704479 hasConcept C81363708 @default.
- W2995704479 hasConceptScore W2995704479C104293457 @default.
- W2995704479 hasConceptScore W2995704479C104317684 @default.
- W2995704479 hasConceptScore W2995704479C11413529 @default.
- W2995704479 hasConceptScore W2995704479C120665830 @default.
- W2995704479 hasConceptScore W2995704479C121332964 @default.
- W2995704479 hasConceptScore W2995704479C154945302 @default.
- W2995704479 hasConceptScore W2995704479C185592680 @default.
- W2995704479 hasConceptScore W2995704479C31972630 @default.
- W2995704479 hasConceptScore W2995704479C41008148 @default.
- W2995704479 hasConceptScore W2995704479C55493867 @default.
- W2995704479 hasConceptScore W2995704479C63479239 @default.
- W2995704479 hasConceptScore W2995704479C81363708 @default.
- W2995704479 hasIssue "S263" @default.
- W2995704479 hasLocation W29957044791 @default.
- W2995704479 hasOpenAccess W2995704479 @default.
- W2995704479 hasPrimaryLocation W29957044791 @default.
- W2995704479 hasRelatedWork W2051487156 @default.
- W2995704479 hasRelatedWork W2073681303 @default.
- W2995704479 hasRelatedWork W2109481748 @default.
- W2995704479 hasRelatedWork W2381719890 @default.
- W2995704479 hasRelatedWork W2417440389 @default.
- W2995704479 hasRelatedWork W2734382758 @default.
- W2995704479 hasRelatedWork W275168305 @default.
- W2995704479 hasRelatedWork W4206096448 @default.
- W2995704479 hasRelatedWork W4378746257 @default.
- W2995704479 hasRelatedWork W4385556839 @default.
- W2995704479 hasVolume "97" @default.
- W2995704479 isParatext "false" @default.
- W2995704479 isRetracted "false" @default.
- W2995704479 magId "2995704479" @default.
- W2995704479 workType "article" @default.