Ophthalmology

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography.

Recently, deep learning-based segmentation models have been widely applied in the ophthalmic field. This study presents the complete process of constructing an orbital computed tomography (CT) segmentation model based on U-Net. For supervised learning, a labor-intensive and time-consuming process is required. The method of labeling with super-resolution to efficiently mask the ground truth on orbi...

3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.

Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and demyelination in the brain, spinal cord, and optic nerve. Optic neuritis, characterized by inflammation and demyelination of the optic nerve, is a symptom in many patients with MS. The optic nerve is the highway for visual information transmitted from the retina to the brain. It contains axons from th...

Portable, Automated and Deep-Learning-Enabled Microscopy for Smartphone-Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review.

Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone-based port...

Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation.

Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and me...

Ultrasound-enhanced catalytic degradation of simulated dye wastewater using waste printed circuit boards: catalytic performance and artificial neuron network-based simulation.

Recent developments of heterogeneous advanced oxidation for refractory organic contaminants and catalysts made of solid waste have attracted much atte...

Comparing the Clinical Viability of Automated Fundus Image Segmentation Methods.

Recent methods for automatic blood vessel segmentation from fundus images have been commonly implemented as convolutional neural networks. While these...

Virtual Impactor-Based Label-Free Pollen Detection using Holography and Deep Learning.

Exposure to bio-aerosols such as pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term mon...

Pterygium Screening and Lesion Area Segmentation Based on Deep Learning.

A two-category model and a segmentation model of pterygium were proposed to assist ophthalmologists in establishing the diagnosis of ophthalmic diseas...

Deep Learning-Assisted Detection of Glaucoma Progression in Spectral-Domain OCT.

PURPOSE: To develop and validate a deep learning (DL) model for detection of glaucoma progression using spectral-domain (SD)-OCT measurements of retin...

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low Vision.

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. C...

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review.

Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldwide. We set out to review the literature on the ap...

Understanding Human Object Vision: A Picture Is Worth a Thousand Representations.

Objects are the core meaningful elements in our visual environment. Classic theories of object vision focus upon object recognition and are elegant an...

Convolutional neural network-based portable computer vision system for freshness assessment of crayfish (Prokaryophyllus clarkii).

Developing novel techniques for freshness assessment are of the utmost importance in yield and trade of aquatic products. The crayfish (Prokaryophyllu...

Deep learning signature of brain [F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder.

An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study ...

VReID: Vision-Outlooker-Based Vehicle Re-Identification.

With the increase of large camera networks around us, it is becoming more difficult to manually identify vehicles. Computer vision enables us to autom...

Assessing visualization in robotic-assisted surgery: demystifying a misty lens.

Despite major technological advancements in robotic-assisted laparoscopic surgery (RAS), there remain shortcomings yet to be addressed. This study ass...

A Deep-Learning Framework for the Automated Recognition of Molecules in Scanning-Probe-Microscopy Images.

Computer vision as a subcategory of deep learning tackles complex vision tasks by dealing with data of images. Molecular images with exceptionally hig...

Combining staged laparoscopic colectomy with robotic completion proctectomy and ileal pouch-anal anastomosis (IPAA) in ulcerative colitis for improved clinical and cosmetic outcomes: a single-center feasibility study and technical description.

Robotic proctectomy has been shown to lead to better functional outcomes compared to laparoscopic surgery in rectal cancer. However, in ulcerative col...

MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.

Accurate retinal blood vessels segmentation is an important step in the clinical diagnosis of ophthalmic diseases. Many deep learning frameworks have ...

Diaphragmatic paralysis post COVID-19 treated with robot-assisted plication reinforced with acellular dermal matrix: a report of two cases.

Coronavirus disease 2019 (COVID-19) continues to be a disease of global importance, with an increasing array of sequelae attributed to infection by th...