Ophthalmology

Human attention guided explainable artificial intelligence for computer vision models.

Explainable artificial intelligence (XAI) has been increasingly investigated to enhance the transpar...

Vision-aided grasp classification: design and evaluation of compact CNN for prosthetic hands.

Powered prosthetic hands capable of executing various grasp patterns are highly sought-after solutio...

Synchronous Diagnosis of Diabetic Retinopathy by a Handheld Retinal Camera, Artificial Intelligence, and Simultaneous Specialist Confirmation.

PURPOSE: Diabetic retinopathy (DR) is a leading cause of preventable blindness, particularly in unde...

Do we really need a large number of visual prompts?

Due to increasing interest in adapting models on resource-constrained edges, parameter-efficient tra...

Screening for urothelial carcinoma cells in urine based on digital holographic flow cytometry through machine learning and deep learning methods.

The incidence of urothelial carcinoma continues to rise annually, particularly among the elderly. Pr...

Deep magnetic resonance fingerprinting based on Local and Global Vision Transformer.

To mitigate systematic errors in magnetic resonance fingerprinting (MRF), the precomputed dictionary...

Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs.

BACKGROUND/OBJECTIVES: Artificial intelligence can assist with ocular image analysis for screening a...

Automated identification of aquatic insects: A case study using deep learning and computer vision techniques.

Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemer...

Deep learning segmentation of non-perfusion area from color fundus images and AI-generated fluorescein angiography.

The non-perfusion area (NPA) of the retina is an important indicator in the visual prognosis of pati...

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and so...

AI in education: A futuristic vision.

Enhancing surgical instrument segmentation: integrating vision transformer insights with adapter.

PURPOSE: In surgical image segmentation, a major challenge is the extensive time and resources requi...

Transforming Poultry Farming: A Pyramid Vision Transformer Approach for Accurate Chicken Counting in Smart Farm Environments.

Smart farm environments, equipped with cutting-edge technology, require proficient techniques for ma...

Artificial intelligence to automate assessment of ocular and periocular measurements.

PURPOSE: To develop and validate a deep learning facial landmark detection network to automate the a...

Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary ou...

Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer's Disease Using 3D Comprehensive Visual Stimuli.

Alzheimer's Disease (AD) is a neurodegenerative disorder that causes a continuous decline in cogniti...

Progression or Aging? A Deep Learning Approach for Distinguishing Glaucoma Progression From Age-Related Changes in OCT Scans.

PURPOSE: To develop deep learning (DL) algorithm to detect glaucoma progression using optical cohere...

Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.

PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (I...

Ensemble learning for retinal disease recognition under limited resources.

Retinal optical coherence tomography (OCT) images provide crucial insights into the health of the po...

G2ViT: Graph Neural Network-Guided Vision Transformer Enhanced Network for retinal vessel and coronary angiograph segmentation.

Blood vessel segmentation is a crucial stage in extracting morphological characteristics of vessels ...

LUNet: deep learning for the segmentation of arterioles and venules in high resolution fundus images.

This study aims to automate the segmentation of retinal arterioles and venules (A/V) from digital fu...