AIMC Topic: Photography

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

Seminars in ophthalmology Feb 22, 2021
Age-related macular degeneration (AMD) affects nearly 200 million people and is the third leading cause of irreversible vision loss worldwide. Deep learning, a branch of artificial intelligence that can learn image recognition based on pre-existing d...
Photography Artificial Intelligence Algorithms Deep Learning Macular Degeneration Humans
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Glaucoma Expert-Level Detection of Angle Closure in Goniophotographs With Convolutional Neural Networks: The Chinese American Eye Study.

American journal of ophthalmology Feb 9, 2021
PURPOSE: To compare the performance of a novel convolutional neural network (CNN) classifier and human graders in detecting angle closure in EyeCam (Clarity Medical Systems, Pleasanton, California, USA) goniophotographs.
Diagnosis, Computer-Assisted China Image Processing, Computer-Assisted Area Under Curve Cross-Sectional Studies Male Middle Aged Ophthalmologists Glaucoma, Angle-Closure Gonioscopy Specialization Expert Systems Asian Photography Anterior Eye Segment Humans Neural Networks, Computer Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over
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Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images.

Burns : journal of the International Society for Burn Injuries Feb 8, 2021
This paper illustrates the efficacy of an artificial intelligence (AI) (a convolutional neural network, based on the U-Net), for the burn-depth assessment using semantic segmentation of polarized high-performance light camera images of burn wounds. T...
Semantics Photography Humans Neural Networks, Computer Artificial Intelligence Child Burns
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Deep Learning for the Diagnosis of Stage in Retinopathy of Prematurity: Accuracy and Generalizability across Populations and Cameras.

Ophthalmology. Retina Feb 6, 2021
PURPOSE: Stage is an important feature to identify in retinal images of infants at risk of retinopathy of prematurity (ROP). The purpose of this study was to implement a convolutional neural network (CNN) for binary detection of stages 1, 2, and 3 in...
Nepal Retinopathy of Prematurity Photography North America Deep Learning ROC Curve Image Processing, Computer-Assisted Area Under Curve Birth Weight Datasets as Topic Reference Standards Gestational Age Humans Female Reproducibility of Results Infant, Newborn Sensitivity and Specificity Male Diagnosis, Computer-Assisted
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Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.

Seminars in ophthalmology Feb 4, 2021
: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost ce...
Photography Humans Diabetic Retinopathy Artificial Intelligence Neural Networks, Computer Machine Learning Algorithms Mass Screening
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Algorithmic and human prediction of success in human collaboration from visual features.

Scientific reports Feb 2, 2021
As groups are increasingly taking over individual experts in many tasks, it is ever more important to understand the determinants of group success. In this paper, we study the patterns of group success in Escape The Room, a physical adventure game in...
Humans Machine Learning Forecasting Photography Facial Recognition Group Processes Female Games, Experimental Male Cues Datasets as Topic
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An objective structural and functional reference standard in glaucoma.

Scientific reports Jan 18, 2021
The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using cle...
Fundus Oculi Optic Nerve Diseases Reference Standards Photography Deep Learning ROC Curve Tomography, Optical Coherence Humans Algorithms Glaucoma Female Male Middle Aged
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Predicting Glaucoma Development With Longitudinal Deep Learning Predictions From Fundus Photographs.

American journal of ophthalmology Jan 7, 2021
PURPOSE: To assess whether longitudinal changes in a deep learning algorithm's predictions of retinal nerve fiber layer (RNFL) thickness based on fundus photographs can predict future development of glaucomatous visual field defects.
Visual Field Tests Photography Fundus Oculi Nerve Fibers Retinal Ganglion Cells Visual Fields Deep Learning Follow-Up Studies Tomography, Optical Coherence Aged Adult Male Middle Aged Humans Glaucoma Retrospective Studies Female
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Universal adversarial attacks on deep neural networks for medical image classification.

BMC medical imaging Jan 7, 2021
BACKGROUND: Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-...
Humans Diabetic Retinopathy Neural Networks, Computer Skin Neoplasms Pneumonia Diagnostic Imaging Photography Tomography, Optical Coherence Image Interpretation, Computer-Assisted Radiography, Thoracic
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Open-Source Automatic Segmentation of Ocular Structures and Biomarkers of Microbial Keratitis on Slit-Lamp Photography Images Using Deep Learning.

IEEE journal of biomedical and health informatics Jan 5, 2021
We propose a fully-automatic deep learning-based algorithm for segmentation of ocular structures and microbial keratitis (MK) biomarkers on slit-lamp photography (SLP) images. The dataset consisted of SLP images from 133 eyes with manual annotations ...
Deep Learning Image Processing, Computer-Assisted Photography Humans Biomarkers Keratitis
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