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
- machine learning
- single molecule
- end stage renal disease
- high resolution
- big data
- newly diagnosed
- ejection fraction
- high speed
- high throughput
- cataract surgery
- prognostic factors
- wound healing
- convolutional neural network
- risk assessment
- label free
- human health
- patient reported
- case control