Ophthalmology

Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-edge technology is limited with reference to the global population. A significant way to improve overall healthcare is to understand the needs and possibilities of all possible consumers when developing sophisticated and accurate medical devices. The S...

Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images.

Central serous chorioretinopathy (CSC) is one of the most common macular diseases that can reduce the quality of life of patients. This study aimed to build a deep learning-based classification model using multiple spectral domain optical coherence tomography (SD-OCT) images together to diagnose CSC. Our proposed system contains two modules: single-image prediction (SIP) and a final decision (FD) ...

Pre-training Model Based on Parallel Cross-Modality Fusion Layer.

Visual Question Answering (VQA) is a learning task that combines computer vision with natural language processing. In VQA, it is important to understa...

How the Brunswikian Lens Model Illustrates the Relationship Between Physiological and Behavioral Signals and Psychological Emotional and Cognitive States.

Social relationships are constructed by and through the relational communication that people exchange. Relational messages are implicit nonverbal and ...

Eye-Tracking Feature Extraction for Biometric Machine Learning.

CONTEXT: Eye tracking is a technology to measure and determine the eye movements and eye positions of an individual. The eye data can be collected and...

A simulation study to investigate the use of concentric tube robots for epilepsy surgery.

PURPOSE: Patients with pharmacoresistant refractory epilepsy may require epilepsy surgery to prevent future seizure occurrences. Conventional surgery ...

The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review.

Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence of diabetes. There are challenges such as the deart...

Asymmetry between right and left fundus images identified using convolutional neural networks.

We analyzed fundus images to identify whether convolutional neural networks (CNNs) can discriminate between right and left fundus images. We gathered ...

Deep Learning Algorithm for Automated Detection of Polycystic Ovary Syndrome Using Scleral Images.

The high prevalence of polycystic ovary syndrome (PCOS) among reproductive-aged women has attracted more and more attention. As a common disorder that...

Glaucoma disease diagnosis with an artificial algae-based deep learning algorithm.

Glaucoma disease is optic neuropathy; in glaucoma, the optic nerve is damaged because the long duration of intraocular pressure can be caused blindnes...

Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.

OBJECTIVE: Digital microscopy is used to monitor particulates such as protein aggregates within biopharmaceutical products. The images that result enc...

Multiple instance learning detects peripheral arterial disease from high-resolution color fundus photography.

Peripheral arterial disease (PAD) is caused by atherosclerosis and is a common disease of the elderly leading to excess morbidity and mortality. Early...

PCAT-UNet: UNet-like network fused convolution and transformer for retinal vessel segmentation.

The accurate segmentation of retinal vessels images can not only be used to evaluate and monitor various ophthalmic diseases, but also timely reflect ...

Clinically applicable deep learning-based decision aids for treatment of neovascular AMD.

PURPOSE: Anti-vascular endothelial growth factor (Anti-VEGF) therapy is currently seen as the standard for treatment of neovascular AMD (nAMD). Howeve...

Twenty seconds of visual behaviour on social media gives insight into personality.

Eye tracking allows the researcher to capture individual differences in the expression of visual exploration behaviour, which in certain contexts has ...

Necessity of Local Modification for Deep Learning Algorithms to Predict Diabetic Retinopathy.

Deep learning (DL) algorithms are used to diagnose diabetic retinopathy (DR). However, most of these algorithms have been trained using global data or...

Variational quantum classifiers through the lens of the Hessian.

In quantum computing, the variational quantum algorithms (VQAs) are well suited for finding optimal combinations of things in specific applications ra...

Indocyanine Green Drives Computer Vision Based 3D Augmented Reality Robot Assisted Partial Nephrectomy: The Beginning of "Automatic" Overlapping Era.

Augmented reality robot-assisted partial nephrectomy (AR-RAPN) is limited by the need of a constant manual overlapping of the hyper-accuracy 3D (HA3D)...

Label-free imaging flow cytometry for analysis and sorting of enzymatically dissociated tissues.

Biomedical research relies on identification and isolation of specific cell types using molecular biomarkers and sorting methods such as fluorescence ...

Microscopic retinal blood vessels detection and segmentation using support vector machine and K-nearest neighbors.

The retina is the deepest layer of texture covering the rear of the eye, recorded by fundus images. Vessel detection and segmentation are useful in di...