Assessing Fuchs Corneal Endothelial Dystrophy Using Artificial Intelligence-Derived Morphometric Parameters From Specular Microscopy Images.
Angelica M PradaFernando QuinteroKevin MendozaVirgilio GalvisAlejandro TelloLenny A RomeroAndres G MarrugoPublished in: Cornea (2024)
This study confirms the utility of CNNs for precise FECD evaluation through specular microscopy. Guttae area ratio emerges as a compelling morphometric parameter aligning closely with modified Krachmer clinical grading. These findings set the stage for future large-scale studies, with potential applications in the assessment of irreversible corneal edema risk after phacoemulsification in FECD patients, as well as in monitoring novel FECD therapies.
Keyphrases
- artificial intelligence
- optical coherence tomography
- deep learning
- end stage renal disease
- machine learning
- single molecule
- big data
- high resolution
- ejection fraction
- chronic kidney disease
- high throughput
- newly diagnosed
- high speed
- endothelial cells
- cataract surgery
- convolutional neural network
- label free
- current status
- climate change