AIMC Topic: Retina
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Comparison between support vector machine and deep learning, machine-learning technologies for detecting epiretinal membrane using 3D-OCT.
International ophthalmology
Sep 14, 2018
PURPOSE: In this study, we compared deep learning (DL) with support vector machine (SVM), both of which use three-dimensional optical coherence tomography (3D-OCT) images for detecting epiretinal membrane (ERM).
Clinically applicable deep learning for diagnosis and referral in retinal disease.
Nature medicine
Aug 13, 2018
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common disease...
A Novel Fundus Image Reading Tool for Efficient Generation of a Multi-dimensional Categorical Image Database for Machine Learning Algorithm Training.
Journal of Korean medical science
Aug 8, 2018
BACKGROUND: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system.
A Neuronal Network Model of the Primate Visual System: Color Mechanisms in the Retina, LGN and V1.
International journal of neural systems
Jul 30, 2018
Color plays a key role in human vision but the neural machinery that underlies the transformation from stimulus to perception is not well understood. Here, we implemented a two-dimensional network model of the first stages in the primate parvocellula...
Supervised Segmentation of Un-Annotated Retinal Fundus Images by Synthesis.
IEEE transactions on medical imaging
Jul 24, 2018
We focus on the practical challenge of segmenting new retinal fundus images that are dissimilar to existing well-annotated data sets. It is addressed in this paper by a supervised learning pipeline, with its core being the construction of a synthetic...
Automated Layer Segmentation of Retinal Optical Coherence Tomography Images Using a Deep Feature Enhanced Structured Random Forests Classifier.
IEEE journal of biomedical and health informatics
Jul 16, 2018
Optical coherence tomography (OCT) is a high-resolution and noninvasive imaging modality that has become one of the most prevalent techniques for ophthalmic diagnosis. Retinal layer segmentation is very crucial for doctors to diagnose and study retin...
RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation.
IEEE journal of biomedical and health informatics
Jul 3, 2018
The level set based deformable models (LDM) are commonly used for medical image segmentation. However, they rely on a handcrafted curve evolution velocity that needs to be adapted for each segmentation task. The Convolutional Neural Networks (CNN) ad...
Structure-Preserving Guided Retinal Image Filtering and Its Application for Optic Disk Analysis.
IEEE transactions on medical imaging
May 21, 2018
Retinal fundus photographs have been used in the diagnosis of many ocular diseases such as glaucoma, pathological myopia, age-related macular degeneration, and diabetic retinopathy. With the development of computer science, computer aided diagnosis h...
Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.
Scientific reports
May 21, 2018
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...
Antiproliferative and anti-apoptotic effect of astaxanthin in an oxygen-induced retinopathy mouse model.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Apr 11, 2018
OBJECTIVE: To evaluate the impact of intravitreal (IV) and intraperitoneal (IP) astaxanthin (AST) injections on neovascular development (ND), retinal morphology, and apoptotic activity in a C57BL/6J mouse model with hyperoxia-induced retinopathy (HIR...
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