AIMC Topic: Retina

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End-to-End Adversarial Retinal Image Synthesis.

IEEE transactions on medical imaging
In medical image analysis applications, the availability of the large amounts of annotated data is becoming increasingly critical. However, annotated medical data is often scarce and costly to obtain. In this paper, we address the problem of synthesi...

Scaling up liquid state machines to predict over address events from dynamic vision sensors.

Bioinspiration & biomimetics
Short-term visual prediction is important both in biology and robotics. It allows us to anticipate upcoming states of the environment and therefore plan more efficiently. In theoretical neuroscience, liquid state machines have been proposed as a biol...

Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy.

PloS one
PURPOSE: Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that using a limited area. We investigated if d...

Development of machine learning models for diagnosis of glaucoma.

PloS one
The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features fro...

Deep image mining for diabetic retinopathy screening.

Medical image analysis
Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert...

Supervised learning and dimension reduction techniques for quantification of retinal fluid in optical coherence tomography images.

Eye (London, England)
PurposeThe purpose of the present study is to develop fast automated quantification of retinal fluid in optical coherence tomography (OCT) image sets.MethodsWe developed an image analysis pipeline tailored towards OCT images that consists of five ste...

A neural network model for visual selection and shifting.

Journal of integrative neuroscience
In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instantaneous frequency. Unlike the differential equation model using limit cycle to simulate neuron oscilla...

Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

Journal of neuroscience methods
BACKGROUND: Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (I...