Ophthalmology

State-of-the-art retinal vessel segmentation with minimalistic models.

The segmentation of retinal vasculature from eye fundus images is a fundamental task in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures have been pushing performance on well-established benchmark datasets. In this paper, we take a step back and analyze the real need of such complexity. We first compile and...

A Photoelectric Spiking Neuron for Visual Depth Perception.

The biological visual system encodes optical information into spikes and processes them by the neural network, which enables the perception with high throughput of visual processing with ultralow energy budget. This has inspired a wide spectrum of devices to imitate such neural process, while precise mimicking such procedure is still highly required. Here, a highly bio-realistic photoelectric spik...

Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database.

Accumulation of beta-amyloid in the brain and cognitive decline are considered hallmarks of Alzheimer's disease. Knowing from previous studies that th...

A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

This paper presents a framework for spiking neural networks to be prepared for the Integrated Information Theory (IIT) analysis, using a stochastic no...

Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.

OBJECTIVE: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techni...

Synergistically segmenting choroidal layer and vessel using deep learning for choroid structure analysis.

. The choroid is the most vascularized structure in the human eye, whose layer structure and vessel distribution are both critical for the physiology ...

Proof-of-Concept Analysis of a Deep Learning Model to Conduct Automated Segmentation of OCT Images for Macular Hole Volume.

BACKGROUND AND OBJECTIVE: To determine whether an automated artificial intelligence (AI) model could assess macular hole (MH) volume on swept-source o...

Computer Vision Positioning and Local Obstacle Avoidance Optimization Based on Neural Network Algorithm.

Due to the rapid development of social computerization and smart devices, there is an increasing demand for indoor positioning of mobile robots in the...

Human-Computer Interaction with Detection of Speaker Emotions Using Convolution Neural Networks.

Emotions play an essential role in human relationships, and many real-time applications rely on interpreting the speaker's emotion from their words. S...

Detection of signs of disease in external photographs of the eyes via deep learning.

Retinal fundus photographs can be used to detect a range of retinal conditions. Here we show that deep-learning models trained instead on external pho...

Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning.

PURPOSE: To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomograph...

A Fully Solution-Printed Photosynaptic Transistor Array with Ultralow Energy Consumption for Artificial-Vision Neural Networks.

Photosynaptic organic field-effect transistors (OFETs) represent a viable pathway to develop bionic optoelectronics. However, the high operating volta...

Diagnostic Accuracy of Artificial Intelligence in Glaucoma Screening and Clinical Practice.

PURPOSE: Artificial intelligence (AI) has been shown as a diagnostic tool for glaucoma detection through imaging modalities. However, these tools are ...

Machine Learning of ZnO Interaction with Immunoglobulins and Blood Proteins in Medicine.

Toxoplasmosis is a zoonotic illness caused by . Those with a normal immune system normally recover without treatment. Immunocompromised individuals an...

Environmentally sustainable development and use of artificial intelligence in health care.

Artificial intelligence (AI) can transform health care by delivering medical services to underserved areas, while also filling gaps in health care pro...

Motion Fatigue State Detection Based on Neural Networks.

Aiming at the problem of fatigue state detection at the back of sports, a cascade deep learning detection system structure is designed, and a convolut...

Motor-related signals support localization invariance for stable visual perception.

Our ability to perceive a stable visual world in the presence of continuous movements of the body, head, and eyes has puzzled researchers in the neuro...

BFENet: A two-stream interaction CNN method for multi-label ophthalmic diseases classification with bilateral fundus images.

BACKGROUND AND OBJECTIVE: Early fundus screening and timely treatment of ophthalmology diseases can effectively prevent blindness. Previous studies ju...

Automated diagnosis of age-related macular degeneration using multi-modal vertical plane feature fusion via deep learning.

PURPOSE: To develop a computer-aided diagnostic (CADx) system of age-related macular degeneration (AMD) through feature fusion between infrared reflec...

Emergence of Direction-Selective Retinal Cell Types in Task-Optimized Deep Learning Models.

Convolutional neural networks (CNNs), a class of deep learning models, have experienced recent success in modeling sensory cortices and retinal circui...