AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cornea

Showing 51 to 60 of 89 articles

Clear Filters

DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity.

IEEE transactions on medical imaging
Accurate estimation and quantification of the corneal nerve fiber tortuosity in corneal confocal microscopy (CCM) is of great importance for disease understanding and clinical decision-making. However, the grading of corneal nerve tortuosity remains ...

Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.

Optics express
We present a parallel Monte Carlo (MC) simulation platform for rapidly generating synthetic common-path optical coherence tomography (CP-OCT) A-scan image dataset for image-guided needle insertion. The computation time of the method has been evaluate...

Segmentation and Evaluation of Corneal Nerves and Dendritic Cells From In Vivo Confocal Microscopy Images Using Deep Learning.

Translational vision science & technology
PURPOSE: Segmentation and evaluation of in vivo confocal microscopy (IVCM) images requires manual intervention, which is time consuming, laborious, and non-reproducible. The aim of this research was to develop and validate deep learning-based methods...

Change patterns in the corneal sub-basal nerve and corneal aberrations in patients with dry eye disease: An artificial intelligence analysis.

Experimental eye research
We aimed to investigate the change patterns in corneal sub-basal nerve morphology and corneal intrinsic aberrations in dry eye disease (DED). Our study included 229 eyes of 155 patients with DED and 40 eyes of 20 healthy control. We used the Oculus k...

A novel combination of corneal confocal microscopy, clinical features and artificial intelligence for evaluation of ocular surface pain.

PloS one
OBJECTIVES: To analyse various corneal nerve parameters using confocal microscopy along with systemic and orthoptic parameters in patients presenting with ocular surface pain using a random forest artificial intelligence (AI) model.

Diagnostic armamentarium of infectious keratitis: A comprehensive review.

The ocular surface
Infectious keratitis (IK) represents the leading cause of corneal blindness worldwide, particularly in developing countries. A good outcome of IK is contingent upon timely and accurate diagnosis followed by appropriate interventions. Currently, IK is...

Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surf...

Artificial intelligence applications in different imaging modalities for corneal topography.

Survey of ophthalmology
Interpretation of topographical maps used to detect corneal ectasias requires a high level of expertise. Several artificial intelligence (AI) technologies have attempted to interpret topographic maps. The purpose of this study is to provide a review ...

A Deep Learning-Based Framework for Accurate Evaluation of Corneal Treatment Zone After Orthokeratology.

Translational vision science & technology
PURPOSE: Given the robust effectiveness of inhibiting myopia progression, orthokeratology has gained increasing popularity worldwide. However, identifying the boundary and the center of reshaped corneal area (i.e., treatment zone) is the main challen...

A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps.

Translational vision science & technology
PURPOSE: To develop and assess the accuracy of a hybrid deep learning construct for detecting keratoconus (KCN) based on corneal topographic maps.