AI Medical Compendium Journal:
Translational vision science & technology

Showing 1 to 10 of 208 articles

Detection of Referable Horizontal Strabismus in Children's Primary Gaze Photographs Using Deep Learning.

Translational vision science & technology
PURPOSE: This study implements and demonstrates a deep learning (DL) approach for screening referable horizontal strabismus based on primary gaze photographs using clinical assessments as a reference. The purpose of this study was to develop and eval...

Predicting Age From Optical Coherence Tomography Scans With Deep Learning.

Translational vision science & technology
PURPOSE: To assess whether age can be predicted from deep learning analysis of peripapillary spectral-domain optical coherence tomography (SD-OCT) B-scans and to determine the importance of specific retinal areas on the predictions.

Deep Learning for Anterior Segment Optical Coherence Tomography to Predict the Presence of Plateau Iris.

Translational vision science & technology
PURPOSE: The purpose of this study was to evaluate the diagnostic performance of deep learning (DL) anterior segment optical coherence tomography (AS-OCT) as a plateau iris prediction model.

Systematic Comparison of Heatmapping Techniques in Deep Learning in the Context of Diabetic Retinopathy Lesion Detection.

Translational vision science & technology
PURPOSE: Heatmapping techniques can support explainability of deep learning (DL) predictions in medical image analysis. However, individual techniques have been mainly applied in a descriptive way without an objective and systematic evaluation. We in...

Deep Learning Model for Accurate Automatic Determination of Phakic Status in Pediatric and Adult Ultrasound Biomicroscopy Images.

Translational vision science & technology
PURPOSE: Ultrasound biomicroscopy (UBM) is a noninvasive method for assessing anterior segment anatomy. Previous studies were prone to intergrader variability, lacked assessment of the lens-iris diaphragm, and excluded pediatric subjects. Lens status...

Classification of Color-Coded Scheimpflug Camera Corneal Tomography Images Using Deep Learning.

Translational vision science & technology
PURPOSE: To assess the use of deep learning for high-performance image classification of color-coded corneal maps obtained using a Scheimpflug camera.

Exploring a Structural Basis for Delayed Rod-Mediated Dark Adaptation in Age-Related Macular Degeneration Via Deep Learning.

Translational vision science & technology
PURPOSE: Delayed rod-mediated dark adaptation (RMDA) is a functional biomarker for incipient age-related macular degeneration (AMD). We used anatomically restricted spectral domain optical coherence tomography (SD-OCT) imaging data to localize de nov...

DeepRetina: Layer Segmentation of Retina in OCT Images Using Deep Learning.

Translational vision science & technology
PURPOSE: To automate the segmentation of retinal layers, we propose DeepRetina, a method based on deep neural networks.

Automatic Identification of Referral-Warranted Diabetic Retinopathy Using Deep Learning on Mobile Phone Images.

Translational vision science & technology
PURPOSE: To evaluate the performance of a deep learning algorithm in the detection of referral-warranted diabetic retinopathy (RDR) on low-resolution fundus images acquired with a smartphone and indirect ophthalmoscope lens adapter.

Identifying Mouse Autoimmune Uveitis from Fundus Photographs Using Deep Learning.

Translational vision science & technology
PURPOSE: To develop a deep learning model for objective evaluation of experimental autoimmune uveitis (EAU), the animal model of posterior uveitis that reveals its essential pathological features via fundus photographs.