AIMC Topic: Retina

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Multi-Expert Deep Networks for Multi-Disease Detection in Retinal Fundus Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Automatic diagnosis of eye diseases from retinal fundus images is quite challenging. Common public datasets include images of subjects with multiple diseases with uneven distribution of labels. Rare diseases are especially challenging due to their un...
Humans Image Processing, Computer-Assisted Fundus Oculi Retina Neural Networks, Computer Algorithms
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A Deep Learning Method for Automatic Identification of Drusen and Macular Hole from Optical Coherence Tomography.

Studies in health technology and informatics May 25, 2022
Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from...
Humans Deep Learning Retinal Diseases Retinal Perforations Tomography, Optical Coherence Retina
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Hybrid-structure network and network comparative study for deep-learning-based speckle-modulating optical coherence tomography.

Optics express May 23, 2022
Optical coherence tomography (OCT), a promising noninvasive bioimaging technique, can resolve sample three-dimensional microstructures. However, speckle noise imposes obvious limitations on OCT resolving capabilities. Here we proposed a deep-learning...
Tomography, Optical Coherence Retina Deep Learning
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Contrast sensitivity functions in autoencoders.

Journal of vision May 3, 2022
Three decades ago, Atick et al. suggested that human frequency sensitivity may emerge from the enhancement required for a more efficient analysis of retinal images. Here we reassess the relevance of low-level vision tasks in the explanation of the co...
Contrast Sensitivity Retina Vision, Ocular Humans Neural Networks, Computer
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SYSTEMATIC CORRELATION OF CENTRAL SUBFIELD THICKNESS WITH RETINAL FLUID VOLUMES QUANTIFIED BY DEEP LEARNING IN THE MAJOR EXUDATIVE MACULAR DISEASES.

Retina (Philadelphia, Pa.) May 1, 2022
PURPOSE: To investigate the correlation of volumetric measurements of intraretinal (IRF) and subretinal fluid obtained by deep learning and central retinal subfield thickness (CSFT) based on optical coherence tomography in retinal vein occlusion, dia...
Retinal Vein Occlusion Retina Macular Edema Humans Diabetic Retinopathy Deep Learning
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Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements.

Translational vision science & technology Apr 1, 2022
PURPOSE: Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learni...
Retinal Diseases Retina Nucleotides Humans Phylogeny Transcription Factors Machine Learning
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Commentary: Artificial intelligence-based screening of retina.

Indian journal of ophthalmology Apr 1, 2022
Artificial Intelligence Mass Screening Retina Humans
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ANALYSIS OF TRANSFER LEARNING FOR SELECT RETINAL DISEASE CLASSIFICATION.

Retina (Philadelphia, Pa.) Jan 1, 2022
PURPOSE: To analyze the effect of transfer learning for classification of diabetic retinopathy (DR) by fundus photography and select retinal diseases by spectral domain optical coherence tomography (SD-OCT).
Deep Learning Tomography, Optical Coherence Algorithms Humans Reproducibility of Results Retina Neural Networks, Computer Retinal Diseases
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EVALUATION OF ARTIFICIAL INTELLIGENCE-BASED QUANTITATIVE ANALYSIS TO IDENTIFY CLINICALLY SIGNIFICANT SEVERE RETINOPATHY OF PREMATURITY.

Retina (Philadelphia, Pa.) Jan 1, 2022
PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP).
Male Severity of Illness Index Deep Learning ROC Curve Female Infant, Newborn Algorithms Humans Retrospective Studies Artificial Intelligence Retinopathy of Prematurity Follow-Up Studies Gestational Age Retina Ophthalmoscopy
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Assessing Vision Quality in Retinal Prosthesis Implantees through Deep Learning: Current Progress and Improvements by Optimizing Hardware Design Parameters and Rehabilitation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Retinal prosthesis (RP) is used to partially restore vision in patients with degenerative retinal diseases. Assessing the quality of RP-acquired (i.e., prosthetic) vision is needed to evaluate RP impact and prospects. Spatial distortions caused by el...
Retina Humans Visual Prosthesis Vision, Ocular Deep Learning Vision, Low
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