AIMC Topic: Photography
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Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.
Eye (London, England)
Jul 2, 2019
OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthal...
Clinical Competence
ROC Curve
Europe
Predictive Value of Tests
Sensitivity and Specificity
Diagnosis, Computer-Assisted
Deep Learning
Photography
Ophthalmologists
Glaucoma, Open-Angle
Optometrists
Observer Variation
Humans
Optic Disk
Artificial Intelligence
Optic Nerve Diseases
Retrospective Studies
False Positive Reactions
Reproducibility of Results
Data fusion strategies for performance improvement of a Process Analytical Technology platform consisting of four instruments: An electrospinning case study.
International journal of pharmaceutics
Jun 26, 2019
The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy,...
Artery-vein segmentation in fundus images using a fully convolutional network.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 15, 2019
Epidemiological studies demonstrate that dimensions of retinal vessels change with ocular diseases, coronary heart disease and stroke. Different metrics have been described to quantify these changes in fundus images, with arteriolar and venular calib...
A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs.
Ophthalmology
Jun 11, 2019
PURPOSE: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).
The role of AI classifiers in skin cancer images.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
May 20, 2019
BACKGROUND: The use of different imaging modalities to assist in skin cancer diagnosis is a common practice in clinical scenarios. Different features representative of the lesion under evaluation can be retrieved from image analysis and processing. H...
Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.
The Lancet. Digital health
May 2, 2019
BACKGROUND: Radical measures are required to identify and reduce blindness due to diabetes to achieve the Sustainable Development Goals by 2030. Therefore, we evaluated the accuracy of an artificial intelligence (AI) model using deep learning in a po...
Photomontage detection using steganography technique based on a neural network.
Neural networks : the official journal of the International Neural Network Society
Apr 17, 2019
This article presents a steganographic method StegoNN based on neural networks. The method is able to identify a photomontage from presented signed images. Unlike other academic approaches using neural networks primarily as classifiers, the StegoNN m...
Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition.
Sensors (Basel, Switzerland)
Mar 31, 2019
In the last decade, deep learning techniques have further improved human activity recognition (HAR) performance on several benchmark datasets. This paper presents a novel framework to classify and analyze human activities. A new convolutional neural ...
Baseball Player Behavior Classification System Using Long Short-Term Memory with Multimodal Features.
Sensors (Basel, Switzerland)
Mar 22, 2019
In this paper, a preliminary baseball player behavior classification system is proposed. By using multiple IoT sensors and cameras, the proposed method accurately recognizes many of baseball players' behaviors by analyzing signals from heterogeneous ...
Sensitivity and specificity of computer vision classification of eyelid photographs for programmatic trachoma assessment.
PloS one
Feb 11, 2019
BACKGROUND/AIMS: Trachoma programs base treatment decisions on the community prevalence of the clinical signs of trachoma, assessed by direct examination of the conjunctiva. Automated assessment could be more standardized and more cost-effective. We ...
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