Ophthalmology

Strabismus Recognition Using Eye-Tracking Data and Convolutional Neural Networks.

Strabismus is one of the most common vision diseases that would cause amblyopia and even permanent vision loss. Timely diagnosis is crucial for well treating strabismus. In contrast to manual diagnosis, automatic recognition can significantly reduce labor cost and increase diagnosis efficiency. In this paper, we propose to recognize strabismus using eye-tracking data and convolutional neural netwo...

Computational mechanisms underlying cortical responses to the affordance properties of visual scenes.

Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and the factors that account for their success are unknown. Here we develop a set of techniques for using CNNs to gain insights into the computational me...

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation.

OBJECTIVE: Deep learning based methods for retinal vessel segmentation are usually trained based on pixel-wise losses, which treat all vessel pixels w...

Open Globe Injury Patient Identification in Warfare Clinical Notes.

The aim of this study is to utilize the Defense and Veterans Eye Injury and Vision Registry clinical data derived from DoD and VA medical systems whic...

A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.

PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding dise...

Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the huma...

A modified artificial neural network based prediction technique for tropospheric radio refractivity.

Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity i...

Using machine-learning to optimize phase contrast in a low-cost cellphone microscope.

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computat...

Flubendiamide induces transgenerational compound eye alterations in .

Pesticides are one of the major sources of environmental toxicity and contamination. This study reports potential of lepidopteran insecticide formulat...

Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.

Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic diagnosis, near-histological visualization, and quan...

Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning.

Methods for aligning 3D fetal neurosonography images must be robust to (i) intensity variations, (ii) anatomical and age-specific differences within t...

Biologically Inspired Intensity and Depth Image Edge Extraction.

In recent years, artificial vision research has moved from focusing on the use of only intensity images to include using depth images, or RGB-D combin...

Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration.

PURPOSE: To predict, by using machine learning, visual acuity (VA) at 3 and 12 months in patients with neovascular age-related macular degeneration (A...

Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks.

Optical Coherence Tomography (OCT) is beco-ming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the nu...

EmotionMeter: A Multimodal Framework for Recognizing Human Emotions.

In this paper, we present a multimodal emotion recognition framework called EmotionMeter that combines brain waves and eye movements. To increase the ...

Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor.

A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledg...

Deep Learning for Computer Vision: A Brief Review.

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with ...

Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception.

This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucl...

Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework.

Most robot navigation systems perform place recognition using a single-sensor modality and one, or at most two heterogeneous map scales. In contrast, ...

Toward an Improvement of the Analysis of Neural Coding.

Machine learning and artificial intelligence have strong roots on principles of neural computation. Some examples are the structure of the first perce...