Volumetric subfield analysis of cynomolgus monkey’s choroid derived from hybrid machine learning optical coherence tomography segmentation
This study aimed to provide volumetric choroidal readings regarding sex, origin, and eye side from healthy cynomolgus monkey eyes as a reference database using optical coherence tomography (OCT) imaging. A machine learning (ML) algorithm was used to extract the choroid from the volumetric OCT data....
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| creator | Maloca, Peter M Valmaggia, Philippe Hartmann, Theresa Juedes, Marlene Hasler, Pascal W Scholl, Hendrik P. N Denk, Nora |
| description | This study aimed to provide volumetric choroidal readings regarding sex, origin, and eye side from healthy cynomolgus monkey eyes as a reference database using optical coherence tomography (OCT) imaging. A machine learning (ML) algorithm was used to extract the choroid from the volumetric OCT data. Classical computer vision methods were then applied to automatically identify the deepest location in the foveolar depression. The choroidal thickness was determined from this reference point. A total of 374 eyes of 203 cynomolgus macaques from Asian and Mauritius origin were included in the analysis. The overall subfoveolar mean choroidal volume in zone 1, in the region of the central bouquet, was 0.156 mm.sup.3 (range, 0.131-0.193 mm.sup.3). For the central choroid volume, the coefficient of variation (CV) was found of 6.3%, indicating relatively little variation. Our results show, based on analyses of variance, that monkey origin (Asian or Mauritius) does not influence choroid volumes. Sex had a significant influence on choroidal volumes in the superior-inferior axis (p [less than or equal to] 0.01), but not in the fovea centralis. A homogeneous foveolar choroidal architecture was also observed. |
| doi_str_mv | 10.1371/journal.pone.0275050 |
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For the central choroid volume, the coefficient of variation (CV) was found of 6.3%, indicating relatively little variation. Our results show, based on analyses of variance, that monkey origin (Asian or Mauritius) does not influence choroid volumes. Sex had a significant influence on choroidal volumes in the superior-inferior axis (p [less than or equal to] 0.01), but not in the fovea centralis. 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N</au><au>Denk, Nora</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Volumetric subfield analysis of cynomolgus monkey’s choroid derived from hybrid machine learning optical coherence tomography segmentation</atitle><jtitle>PloS one</jtitle><date>2022-09-23</date><risdate>2022</risdate><volume>17</volume><issue>9</issue><spage>e0275050</spage><epage>e0275050</epage><pages>e0275050-e0275050</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>This study aimed to provide volumetric choroidal readings regarding sex, origin, and eye side from healthy cynomolgus monkey eyes as a reference database using optical coherence tomography (OCT) imaging. A machine learning (ML) algorithm was used to extract the choroid from the volumetric OCT data. Classical computer vision methods were then applied to automatically identify the deepest location in the foveolar depression. The choroidal thickness was determined from this reference point. 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| subjects | Algorithms Analysis Biology and Life Sciences Coefficient of variation Coherence (Optics) Computer and Information Sciences Computer vision Correlation analysis Deep learning Eye Fovea Health aspects Image segmentation Laboratories Learning algorithms Machine learning Medicine and Health Sciences Methods Monkeys Morphology Optical Coherence Tomography Optical tomography Physical Sciences Product development Research and Analysis Methods Retina Semantics Sex Tomography Variance analysis |
| title | Volumetric subfield analysis of cynomolgus monkey’s choroid derived from hybrid machine learning optical coherence tomography segmentation |
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