AIMC Topic: Fundus Oculi
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Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks.
Current eye research
Apr 6, 2021
: This study developed and evaluated a deep learning ensemble method to automatically grade the stages of glaucoma depending on its severity.: After cross-validation of three glaucoma specialists, the final dataset comprised of 3,460 fundus photograp...
Development and evaluation of a deep learning model for the detection of multiple fundus diseases based on colour fundus photography.
The British journal of ophthalmology
Mar 30, 2021
AIM: To explore and evaluate an appropriate deep learning system (DLS) for the detection of 12 major fundus diseases using colour fundus photography.
Machine learning prediction of pathologic myopia using tomographic elevation of the posterior sclera.
Scientific reports
Mar 26, 2021
Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in defining the classification of the degree or extent of early disease, such that it may be biased by s...
Fast and efficient retinal blood vessel segmentation method based on deep learning network.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 16, 2021
The segmentation of the retinal vascular tree presents a major step for detecting ocular pathologies. The clinical context expects higher segmentation performance with a reduced processing time. For higher accurate segmentation, several automated met...
Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 25, 2021
Multimodal retinal imaging plays an important role in ophthalmology. We propose a content-adaptive multimodal retinal image registration method in this paper that focuses on the globally coarse alignment and includes three weakly supervised neural ne...
Development of a deep-learning system for detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus images: a pilot study.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Feb 4, 2021
PURPOSE: To investigate the detection of lattice degeneration, retinal breaks, and retinal detachment in tessellated eyes using ultra-wide-field fundus imaging system (Optos) with convolutional neural network technology.
Transformation-Consistent Self-Ensembling Model for Semisupervised Medical Image Segmentation.
IEEE transactions on neural networks and learning systems
Feb 4, 2021
A common shortfall of supervised deep learning for medical imaging is the lack of labeled data, which is often expensive and time consuming to collect. This article presents a new semisupervised method for medical image segmentation, where the networ...
Skin Diseases
Dermatology
Optic Disk
Databases, Factual
Diagnostic Imaging
Tomography, X-Ray Computed
Fundus Oculi
Reproducibility of Results
Supervised Machine Learning
Image Processing, Computer-Assisted
Liver
Neural Networks, Computer
Deep Learning
Humans
Glaucoma
Imaging, Three-Dimensional
Algorithms
A combined convolutional and recurrent neural network for enhanced glaucoma detection.
Scientific reports
Jan 21, 2021
Glaucoma, a leading cause of blindness, is a multifaceted disease with several patho-physiological features manifesting in single fundus images (e.g., optic nerve cupping) as well as fundus videos (e.g., vascular pulsatility index). Current convoluti...
Applications of deep learning in fundus images: A review.
Medical image analysis
Jan 20, 2021
The use of fundus images for the early screening of eye diseases is of great clinical importance. Due to its powerful performance, deep learning is becoming more and more popular in related applications, such as lesion segmentation, biomarkers segmen...
An objective structural and functional reference standard in glaucoma.
Scientific reports
Jan 18, 2021
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using cle...
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