Ophthalmology

Densely connected U-Net retinal vessel segmentation algorithm based on multi-scale feature convolution extraction.

PURPOSE: The segmentation results of retinal blood vessels have a significant impact on the automatic diagnosis of various ophthalmic diseases. In order to further improve the segmentation accuracy of retinal vessels, we propose an improved algorithm based on multiscale vessel detection, which extracts features through densely connected networks and reuses features.

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and Wavelet Transform-Support Vector Machine (WT-SVM) algorithm. Considering the poor deformability and biocompatibility of rigid metal electrodes, we propose a flexible hydrogel biosensor made of conductive HPC/PVA (Hy...

A Novel Automatic Morphologic Analysis of Eyelids Based on Deep Learning Methods.

: To propose a deep-learning-based approach to automatically and objectively evaluate morphologic eyelid features using two-dimensional(2D) digital ph...

A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans.

The objective quantification of retinal atrophy associated with age-related macular degeneration (AMD) is required for clinical diagnosis, follow-up, ...

Quantitative gait analysis of idiopathic normal pressure hydrocephalus using deep learning algorithms on monocular videos.

A vision-based gait analysis method using monocular videos was proposed to estimate temporo-spatial gait parameters by leveraging deep learning algori...

Vision-Based Tunnel Lining Health Monitoring via Bi-Temporal Image Comparison and Decision-Level Fusion of Change Maps.

Tunnel structural health inspections are predominantly done through periodic visual observations, requiring humans to be physically present on-site, p...

An eye-tracking based robotic scrub nurse: proof of concept.

BACKGROUND: Within surgery, assistive robotic devices (ARD) have reported improved patient outcomes. ARD can offer the surgical team a "third hand" to...

Development and application of the ocular immune-mediated inflammatory diseases ontology enhanced with synonyms from online patient support forum conversation.

BACKGROUND: Unstructured text created by patients represents a rich, but relatively inaccessible resource for advancing patient-centred care. This stu...

Responsibility beyond design: Physicians' requirements for ethical medical AI.

Medical AI is increasingly being developed and tested to improve medical diagnosis, prediction and treatment of a wide array of medical conditions. De...

A high resolution representation network with multi-path scale for retinal vessel segmentation.

BACKGROUND AND OBJECTIVES: Automatic retinal vessel segmentation (RVS) in fundus images is expected to be a vital step in the early image diagnosis of...

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients.

Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate diagnosis can improve the analysis and prognosis of ...

A Global and Local Enhanced Residual U-Net for Accurate Retinal Vessel Segmentation.

Retinal vessel segmentation is a critical procedure towards the accurate visualization, diagnosis, early treatment, and surgery planning of ocular dis...

A deep transfer learning framework for the automated assessment of corneal inflammation on in vivo confocal microscopy images.

PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. ...

Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology.

Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we...

Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc...

An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning.

Diabetic retinopathy occurs as a result of the harmful effects of diabetes on the eyes. Diabetic retinopathy is also a disease that should be diagnose...

Real-time, automatic, open-source sleep stage classification system using single EEG for mice.

We developed a real-time sleep stage classification system with a convolutional neural network using only a one-channel electro-encephalogram source f...

Diabetic Retinopathy Fundus Image Classification and Lesions Localization System Using Deep Learning.

Diabetic retinopathy (DR) is a disease resulting from diabetes complications, causing non-reversible damage to retina blood vessels. DR is a leading c...

Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs.

OBJECTIVE: To evaluate the performance of a deep learning system (DLS) in classifying the severity of papilledema associated with increased intracrani...

Artificial intelligence extension of the OSCAR-IB criteria.

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological di...