Ophthalmology

Latest AI and machine learning research in ophthalmology for healthcare professionals.

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Generative Adversarial Network Technologies and Applications in Computer Vision.

Computer vision is one of the hottest research fields in deep learning. The emergence of generative adversarial networks (GANs) provides a new method and model for computer vision. The idea of GANs using the game training method is superior to traditional machine learning algorithms in terms of feature learning and image generation. GANs are widely used not only in image generation and style trans...

Aug 1 2020 32802024

A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.

Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differences based on different networks driven by different tasks. Here, the impact of network tasks on encoding models is studied. Using functional magnetic...

Aug 1 2020 32802150
Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning.

Artificial intelligence has recently made a disruptive impact in medical imaging by successfully automatizing expert-level diagnostic tasks. However, ...

Jul 31 2020 32737379
The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot Interaction.

The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutu...

Jul 31 2020 32752008
Fully Automatic Arteriovenous Segmentation in Retinal Images via Topology-Aware Generative Adversarial Networks.

Retinal image contains rich information on the blood vessel and is highly related to vascular diseases. Fully automatic and accurate identification of...

Jul 28 2020 32725575
Automatic Segmentation of Retinal Capillaries in Adaptive Optics Scanning Laser Ophthalmoscope Perfusion Images Using a Convolutional Neural Network.

PURPOSE: Adaptive optics scanning laser ophthalmoscope (AOSLO) capillary perfusion images can possess large variations in contrast, intensity, and bac...

Jul 23 2020 32855847
An Interactive Visualization for Feature Localization in Deep Neural Networks.

Deep artificial neural networks have become the go-to method for many machine learning tasks. In the field of computer vision, deep convolutional neur...

Jul 23 2020 33733166
A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression.

UNLABELLED: Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of art...

Jul 22 2020 32855846
Lightweight Learning-Based Automatic Segmentation of Subretinal Blebs on Microscope-Integrated Optical Coherence Tomography Images.

PURPOSE: Subretinal injections of therapeutics are commonly used to treat ocular diseases. Accurate dosing of therapeutics at target locations is cruc...

Jul 21 2020 32707207
Neurolight: A Deep Learning Neural Interface for Cortical Visual Prostheses.

Visual neuroprosthesis, that provide electrical stimulation along several sites of the human visual system, constitute a potential tool for vision res...

Jul 21 2020 32689842
Computer Vision-Based Grasp Pattern Recognition With Application to Myoelectric Control of Dexterous Hand Prosthesis.

Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achieve suitable grasps over various objects, a novel co...

Jul 20 2020 32746315
The understanding of congruent and incongruent referential gaze in 17-month-old infants: an eye-tracking study comparing human and robot.

Several studies have shown that the human gaze, but not the robot gaze, has significant effects on infant social cognition and facilitate social engag...

Jul 17 2020 32681110
Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy.

PURPOSE: To improve disease severity classification from fundus images using a hybrid architecture with symptom awareness for diabetic retinopathy (DR...

Jul 16 2020 32855845
Added value of 3D-vision during robotic pancreatoduodenectomy anastomoses in biotissue (LAEBOT 3D2D): a randomized controlled cross-over trial.

BACKGROUND: We tested the added value of 3D-vision on procedure time and surgical performance during robotic pancreatoduodenectomy anastomoses in biot...

Jul 13 2020 32661707
Advances in Telemedicine in Ophthalmology.

Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into th...

Jul 9 2020 32644878
Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.

The aim of this study is to investigate the usefulness of the anomaly detection method by one-class support vector machine (OCSVM) for the evaluation ...

Jul 6 2020 32658775
Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning.

BACKGROUND: Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to the small blood vessels in the retina. If untreate...

Jul 6 2020 32631221
Pupil Localisation and Eye Centre Estimation Using Machine Learning and Computer Vision.

Various methods have been used to estimate the pupil location within an image or a real-time video frame in many fields. However, these methods lack t...

Jul 6 2020 32640589
Artificial intelligence method to classify ophthalmic emergency severity based on symptoms: a validation study.

OBJECTIVES: We investigated the usefulness of machine learning artificial intelligence (AI) in classifying the severity of ophthalmic emergency for ti...

Jul 5 2020 32624476
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