Ophthalmology

Comment on: Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

NeuroGen: Activation optimized image synthesis for discovery neuroscience.

Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a priori hypotheses, limited to the set of images presented to the individual while they are in the scanner, are subject to noise in the observed brain responses, and may vary widely across individuals. In this work, we propos...

Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks.

This article presents a systematic overview of artificial intelligence (AI) and computer vision strategies for diagnosing the coronavirus disease of 2...

Automated tool detection with deep learning for monitoring kinematics and eye-hand coordination in microsurgery.

In microsurgical procedures, surgeons use micro-instruments under high magnifications to handle delicate tissues. These procedures require highly skil...

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice.

An increasing number of artificial intelligence (AI) systems are being proposed in ophthalmology, motivated by the variety and amount of clinical and ...

Change patterns in the corneal sub-basal nerve and corneal aberrations in patients with dry eye disease: An artificial intelligence analysis.

We aimed to investigate the change patterns in corneal sub-basal nerve morphology and corneal intrinsic aberrations in dry eye disease (DED). Our stud...

Robust Perturbation for Visual Explanation: Cross-Checking Mask Optimization to Avoid Class Distortion.

Along with the outstanding performance of the deep neural networks (DNNs), considerable research efforts have been devoted to finding ways to understa...

Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images.

Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims...

Predictive Control-Based Completeness Analysis and Global Calibration of Robot Vision Features.

This paper provides an in-depth study and analysis of robot vision features for predictive control and a global calibration of their feature completen...

Weakly Supervised Sensitive Heatmap framework to classify and localize diabetic retinopathy lesions.

Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase ...

Cataract Disease Detection by Using Transfer Learning-Based Intelligent Methods.

One of the most common visual disorders is cataracts, which people suffer from as they get older. The creation of a cloud on the lens of our eyes is k...

Event-Based Vision: A Survey.

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously m...

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medic...

Novel computational models offer alternatives to animal testing for assessing eye irritation and corrosion potential of chemicals.

Eye irritation and corrosion are fundamental considerations in developing chemicals to be used in or near the eye, from cleaning products to ophthalmi...

RFARN: Retinal vessel segmentation based on reverse fusion attention residual network.

Accurate segmentation of retinal vessels is critical to the mechanism, diagnosis, and treatment of many ocular pathologies. Due to the poor contrast a...

A brain extraction algorithm for infant T2 weighted magnetic resonance images based on fuzzy c-means thresholding.

It is challenging to extract the brain region from T2-weighted magnetic resonance infant brain images because conventional brain segmentation algorith...

Newborn Eye Screening as an Application of AI.

Artificial intelligence (AI) applications are diverse and serve varied functions in clinical practice. The most successful products today are clinical...

Vision-Based Driver's Cognitive Load Classification Considering Eye Movement Using Machine Learning and Deep Learning.

Due to the advancement of science and technology, modern cars are highly technical, more activity occurs inside the car and driving is faster; however...

Knowledge Gaps: A Challenge for Agent-Based Automatic Task Completion.

The study of human cognition and the study of artificial intelligence (AI) have a symbiotic relationship, with advancements in one field often informi...

Robotic Extended Ultrasound-Guided Distal Pancreatectomy for Pancreatic Metastases from Uveal Melanoma.

BACKGROUND: Isolated pancreatic metastasis from melanoma is extremely uncommon and accounts for approximately only 2% of visceral disseminations of me...