Ophthalmology

Deep learning models for benign and malign ocular tumor growth estimation.

Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image processing methods. Clinicians often face issues in selecting suitable image processing algorithm for medical imaging data. A strategy for the selection of a proper model is presented here. The training data set comprises optical coherence tomograph...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rate and accuracy of diagnosis of colorectal polyp which vary in different experienced endoscopists have impact on the colonoscopy protection effect of CRC. The work proposed a colorectal polyp image detection and classification system through grayscale...

Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.

With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection ...

Human-Machine Interface: Multiclass Classification by Machine Learning on 1D EOG Signals for the Control of an Omnidirectional Robot.

People with severe disabilities require assistance to perform their routine activities; a Human-Machine Interface (HMI) will allow them to activate de...

Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer vision.

In this paper, we capture and explore the painterly depictions of materials to enable the study of depiction and perception of materials through the a...

Artificial Vision Algorithms for Socially Assistive Robot Applications: A Review of the Literature.

Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status ...

Losartan as a Steroid-Sparing Adjunct in a Patient With Features of Refractory Camurati-Engelmann Disease.

OBJECTIVE: The treatment of Camurati-Engelmann disease (CED) involves the use of glucocorticoids, analgesics, and bisphosphonates; experience with the...

Transcorneal delivery of topically applied silver nanoparticles does not delay epithelial wound healing.

Silver nanoparticles (AgNPs) are a common antimicrobial additive for a variety of applications, including wound care. However, AgNPs often undergo dis...

Prediction Algorithm of Young Students' Physical Health Risk Factors Based on Deep Learning.

Young people's physical and mental health is the foundation of society's overall development and the key to improving people's health quality. Middle ...

Imaging and artificial intelligence for progression of age-related macular degeneration.

Age-related macular degeneration (AMD) is a leading cause of severe vision loss. With our aging population, it may affect 288 million people globally ...

Automatic detection of pathological myopia using machine learning.

Pathological myopia is a severe case of myopia, i.e., nearsightedness. Pathological myopia is also known as degenerative myopia because it ultimately ...

Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image ...

Tunable Soft Lens of Large Focal Length Change.

Tunable lens technology inspired by the human eye has opened a new paradigm of smart optical devices for a variety of applications due to unique chara...

Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN.

Early detection of disease genes helps humans to recover from certain gene-related diseases, like genetic eye diseases. This work identifies the possi...

Fast and Accurate Ophthalmic Medication Bottle Identification Using Deep Learning on a Smartphone Device.

PURPOSE: To assess the accuracy and efficacy of deep learning models, specifically convolutional neural networks (CNNs), to identify glaucoma medicati...

Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.

Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep lear...

DeepFoveaNet: Deep Fovea Eagle-Eye Bioinspired Model to Detect Moving Objects.

Birds of prey especially eagles and hawks have a visual acuity two to five times better than humans. Among the peculiar characteristics of their biolo...

Attention-based deep learning system for automated diagnoses of age-related macular degeneration in optical coherence tomography images.

PURPOSE: The progression of age-related macular degeneration (AMD) is critical to treatment decisions in clinical practice. The disease can be classif...

Extended Spatially Localized Perturbation GAN (eSLP-GAN) for Robust Adversarial Camouflage Patches.

Deep neural networks (DNNs), especially those used in computer vision, are highly vulnerable to adversarial attacks, such as adversarial perturbations...

Neovascularization Detection and Localization in Fundus Images Using Deep Learning.

Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patients. It is characterized by neovascularization in th...