AIMC Topic: Retina

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Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning.

Investigative ophthalmology & visual science Oct 1, 2016
PURPOSE: To compare performance of a deep-learning enhanced algorithm for automated detection of diabetic retinopathy (DR), to the previously published performance of that algorithm, the Iowa Detection Program (IDP)-without deep learning components-o...
Humans ROC Curve Follow-Up Studies Diagnosis, Computer-Assisted Diagnostic Techniques, Ophthalmological Ophthalmologists Automation Retina Female Retrospective Studies Middle Aged Male Neural Networks, Computer Algorithms Diabetic Retinopathy
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Lion's Mane, Hericium erinaceus and Tiger Milk, Lignosus rhinocerotis (Higher Basidiomycetes) Medicinal Mushrooms Stimulate Neurite Outgrowth in Dissociated Cells of Brain, Spinal Cord, and Retina: An In Vitro Study.

International journal of medicinal mushrooms Jan 1, 2015
Neurodegenerative disease is defined as a deterioration of the nervous system in the intellectual and cognitive capabilities. Statistics show that more than 80-90 million individuals age 65 and above in 2050 may be affected by neurodegenerative condi...
Polyporales Cell Survival Retina Rats Brain In Vitro Techniques Neurites Cells, Cultured Animals Plant Extracts PC12 Cells Chickens Spinal Cord Basidiomycota
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Ontogenic retinal changes in three ecologically distinct elopomorph fishes (Elopomorpha:Teleostei) correlate with light environment and behavior.

Visual neuroscience Jan 1, 2015
Unlike the mammalian retina, the teleost fish retina undergoes persistent neurogenesis from intrinsic stem cells. In marine teleosts, most cone photoreceptor genesis occurs early in the embryonic and larval stages, and rods are added primarily during...
Retinal Rod Photoreceptor Cells Light Visual Acuity Fishes Retina Metamorphosis, Biological Animals Biological Ontologies Environment Larva Species Specificity Retinal Cone Photoreceptor Cells Ecology Opsins
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Predicting Semantic Descriptions from Medical Images with Convolutional Neural Networks.

Information processing in medical imaging : proceedings of the ... conference Jan 1, 2015
Learning representative computational models from medical imaging data requires large training data sets. Often, voxel-level annotation is unfeasible for sufficient amounts of data. An alternative to manual annotation, is to use the enormous amount o...
Image Interpretation, Computer-Assisted Semantics Retina Retinal Diseases Image Enhancement Pattern Recognition, Automated Reproducibility of Results Algorithms Tomography, Optical Coherence Sensitivity and Specificity Humans Neural Networks, Computer
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