AIMC Topic: Corneal Pachymetry

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Thickness Speed Progression Index: Machine Learning Approach for Keratoconus Detection.

American journal of ophthalmology Nov 27, 2024
PURPOSE: To develop and validate a pachymetry-based machine learning (ML) index for differentiating keratoconus, keratoconus suspect, and normal corneas.
Reproducibility of Results Young Adult Adult Cornea Machine Learning Humans Algorithms Retrospective Studies Female Male ROC Curve Middle Aged Keratoconus Disease Progression Corneal Topography Adolescent Corneal Pachymetry
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Corneal Topography Raw Data Classification Using a Convolutional Neural Network.

American journal of ophthalmology Jun 10, 2020
PURPOSE: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS).
Humans Middle Aged Refractive Errors Refractive Surgical Procedures Reproducibility of Results Neural Networks, Computer Keratoconus Healthy Volunteers Adult Corneal Topography Machine Learning Corneal Pachymetry Sensitivity and Specificity Retrospective Studies Male Female
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Multi-view deep learning for rigid gas permeable lens base curve fitting based on Pentacam images.

Medical & biological engineering & computing May 3, 2020
Many studies in the rigid gas permeable (RGP) lens fitting field have focused on providing the best fit for patients with irregular astigmatism, a challenging issue. Despite the ease and accuracy of fitting in the current fitting methods, no studies ...
Contact Lenses Corneal Pachymetry Contact Lenses, Extended-Wear Humans Neural Networks, Computer Deep Learning Astigmatism
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The Role of Corneal Biomechanics for the Evaluation of Ectasia Patients.

International journal of environmental research and public health Mar 23, 2020
PURPOSE: To review the role of corneal biomechanics for the clinical evaluation of patients with ectatic corneal diseases.
ROC Curve Corneal Topography Germany Corneal Pachymetry Artificial Intelligence Retrospective Studies Dilatation, Pathologic Cornea Humans
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Enhanced Tomographic Assessment to Detect Corneal Ectasia Based on Artificial Intelligence.

American journal of ophthalmology Aug 9, 2018
PURPOSE: To improve the detection of corneal ectasia susceptibility using tomographic data.
Sensitivity and Specificity Dilatation, Pathologic Cornea Male Middle Aged Case-Control Studies ROC Curve Keratoconus Artificial Intelligence Retrospective Studies Female Adult Humans Corneal Topography Corneal Pachymetry Diagnostic Techniques, Ophthalmological Slit Lamp Microscopy Keratomileusis, Laser In Situ Tomography
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[Assistant diagnose for subclinical keratoconus by artificial intelligence].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology Dec 11, 2019
To investigate the diagnosis of normal cornea, subclinical keratoconus and keratoconus by artifical intelligence. Diagnostic study. From January 2016 to January 2019, who admitted to Tianjin Eye Hospital from 18 to 48 years old, with an average of ...
Corneal Topography Corneal Pachymetry Young Adult Adult Sensitivity and Specificity Cornea Middle Aged Adolescent ROC Curve Keratoconus Humans Artificial Intelligence
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Corneal thickness measurement by secondary speckle tracking and image processing using machine-learning algorithms.

Journal of biomedical optics Dec 1, 2019
Corneal thickness (CoT) is an important tool in the evaluation process for several disorders and in the assessment of intraocular pressure. We present a method enabling high-precision measurement of CoT based on secondary speckle tracking and process...
Young Adult Adult Cornea Middle Aged Image Interpretation, Computer-Assisted Phantoms, Imaging Corneal Pachymetry Neural Networks, Computer Machine Learning Algorithms Humans Aged
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Evaluation of a Machine-Learning Classifier for Keratoconus Detection Based on Scheimpflug Tomography.

Cornea Jun 1, 2016
PURPOSE: To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with othe...
Diagnostic Techniques, Ophthalmological Corneal Pachymetry Algorithms Middle Aged Humans Retrospective Studies Young Adult Adolescent Female Machine Learning Adult Keratoconus Reproducibility of Results Corneal Topography Sensitivity and Specificity Male
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Accuracy of machine learning classifiers using bilateral data from a Scheimpflug camera for identifying eyes with preclinical signs of keratoconus.

Journal of cataract and refractive surgery Feb 1, 2016
PURPOSE: To describe the topographic and tomographic characteristics of normal fellow eyes of unilateral keratoconus cases and to evaluate the accuracy of machine learning classifiers in discriminating healthy corneas from the normal fellow corneas.
Photography Corneal Pachymetry Cornea Female ROC Curve Male Humans Keratoconus Middle Aged Reproducibility of Results Machine Learning Corneal Topography Case-Control Studies Young Adult Retrospective Studies Diagnostic Techniques, Ophthalmological Adult
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