Ophthalmology

Subfoveal choroidal thickness changes after intravitreal ranibizumab injections in different patterns of diabetic macular edema using a deep learning-based auto-segmentation.

PURPOSE: To evaluate the effect of intravitreal injection of ranibizumab (IVR) on subfoveal choroidal thickness (SFCT) and its relationship with central macular thickness (CMT) and best-corrected visual acuity (BCVA) changes in eyes with center-involving DME (CI-DME) using a deep learning-based auto-segmentation.

Deep learning and ensemble stacking technique for differentiating polypoidal choroidal vasculopathy from neovascular age-related macular degeneration.

Polypoidal choroidal vasculopathy (PCV) and neovascular age-related macular degeneration (nAMD) share some similarity in clinical imaging manifestations. However, their disease entity and treatment strategy as well as visual outcomes are very different. To distinguish these two vision-threatening diseases is somewhat challenging but necessary. In this study, we propose a new artificial intelligenc...

Real-time face & eye tracking and blink detection using event cameras.

Event cameras contain emerging, neuromorphic vision sensors that capture local-light​ intensity changes at each pixel, generating a stream of asynchro...

Machine learning prediction of pathologic myopia using tomographic elevation of the posterior sclera.

Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in d...

AI-based structure-function correlation in age-related macular degeneration.

Sensitive and robust outcome measures of retinal function are pivotal for clinical trials in age-related macular degeneration (AMD). A recent developm...

Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development.

We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye-track...

Reconstructing feedback representations in the ventral visual pathway with a generative adversarial autoencoder.

While vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward...

Artificial intelligence in OCT angiography.

Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, information-rich vascular images....

Artificial Intelligence (AI) and Retinal Optical Coherence Tomography (OCT).

Ophthalmology has been at the forefront of medical specialties adopting artificial intelligence. This is primarily due to the "image-centric" nature o...

Fast and efficient retinal blood vessel segmentation method based on deep learning network.

The segmentation of the retinal vascular tree presents a major step for detecting ocular pathologies. The clinical context expects higher segmentation...

Is artificial intelligence a solution to the myopia pandemic?

Deep Learning-Based Diabetic Retinopathy Severity Grading System Employing Quadrant Ensemble Model.

The diabetic retinopathy accounts in the deterioration of retinal blood vessels leading to a serious compilation affecting the eyes. The automated DR ...

Towards Robust Robot Control in Cartesian Space Using an Infrastructureless Head- and Eye-Gaze Interface.

This paper presents a lightweight, infrastructureless head-worn interface for robust and real-time robot control in Cartesian space using head- and ey...

Effects of Image Degradation and Degradation Removal to CNN-Based Image Classification.

Just like many other topics in computer vision, image classification has achieved significant progress recently by using deep learning neural networks...

Hierarchical deep learning models using transfer learning for disease detection and classification based on small number of medical images.

Deep learning is being employed in disease detection and classification based on medical images for clinical decision making. It typically requires la...

A study on CNN image classification of EEG signals represented in 2D and 3D.

The novelty of this study consists of the exploration of multiple new approaches of data pre-processing of brainwave signals, wherein statistical feat...

Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework.

Multimodal retinal imaging plays an important role in ophthalmology. We propose a content-adaptive multimodal retinal image registration method in thi...

Application of Deep Learning for Diagnosing, Classifying, and Treating Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) affects nearly 200 million people and is the third leading cause of irreversible vision loss worldwide. Deep le...

Practices and Applications of Convolutional Neural Network-Based Computer Vision Systems in Animal Farming: A Review.

Convolutional neural network (CNN)-based computer vision systems have been increasingly applied in animal farming to improve animal management, but cu...

Deep Learning Approach for Automated Detection of Myopic Maculopathy and Pathologic Myopia in Fundus Images.

PURPOSE: To determine whether eyes with pathologic myopia can be identified and whether each type of myopic maculopathy lesion on fundus photographs c...