AIMC Topic: Retina

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Image processing and supervised machine learning for retinal microglia characterization in senescence.

Methods in cell biology
The process of senescence impairs the function of cells and can ultimately be a key factor in the development of disease. With an aging population, senescence-related diseases are increasing in prevalence. Therefore, understanding the mechanisms of c...

Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Scientific reports
Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existing automated algorithms have mostly been developed from images acquired with high cost mydriatic ret...

Prediction of Visual Impairment in Epiretinal Membrane and Feature Analysis: A Deep Learning Approach Using Optical Coherence Tomography.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: The aim was to develop a deep learning model for predicting the extent of visual impairment in epiretinal membrane (ERM) using optical coherence tomography (OCT) images, and to analyze the associated features.

Context encoder transfer learning approaches for retinal image analysis.

Computers in biology and medicine
During the last years, deep learning techniques have emerged as powerful alternatives to solve biomedical image analysis problems. However, the training of deep neural networks usually needs great amounts of labeled data to be done effectively. This ...

Robot-assisted subretinal injection system: development and preliminary verification.

BMC ophthalmology
BACKGROUND: To design and develop a surgical robot capable of assisting subretinal injection.

Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Age-related macular degeneration (AMD) is a degenerative disorder affecting the macula, a key area of the retina for visual acuity. Nowadays, AMD is the most frequent cause of blindness in developed countries. Although some...

MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.

Computational intelligence and neuroscience
Accurate retinal blood vessels segmentation is an important step in the clinical diagnosis of ophthalmic diseases. Many deep learning frameworks have come up for retinal blood vessels segmentation tasks. However, the complex vascular structure and un...

Efficient and Consistent Generation of Retinal Pigment Epithelium/Choroid Flatmounts from Human Eyes for Histological Analysis.

Journal of visualized experiments : JoVE
The retinal pigment epithelium (RPE) and retina are functionally and structurally connected tissues that work together to regulate light perception and vision. Proteins on the RPE apical surface are tightly associated with proteins on the photorecept...

Prior optic neuritis detection on peripapillary ring scans using deep learning.

Annals of clinical and translational neurology
BACKGROUND: The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes...

An automated unsupervised deep learning-based approach for diabetic retinopathy detection.

Medical & biological engineering & computing
As per the International Diabetes Federation (IDF) report, 35-60% of people suffering from diabetic retinopathy (DR) have a history of diabetes. DR is one of the primary reasons for blindness and visual impairment worldwide among adults aged 24-74 ye...