AIMC Topic: Macular Degeneration
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Artificial intelligence-based decision-making for age-related macular degeneration.
Theranostics
Jan 1, 2019
Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-base...
Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans.
Computers in biology and medicine
Dec 31, 2018
Maculopathy is a group of retinal disorders that affect macula and cause severe visual impairment if not treated in time. Many computer-aided diagnostic methods have been proposed over the past that automatically detect macular diseases. However, to ...
Can Artificial Intelligence Make Screening Faster, More Accurate, and More Accessible?
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Dec 17, 2018
Diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes of vision loss and blindness worldwide. They tend to be asymptomatic in the early phase of disease and therefore require active screening programs to identify the...
Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.
Clinical & experimental ophthalmology
Nov 15, 2018
IMPORTANCE: Artificial intelligence (AI) algorithms are under development for use in diabetic retinopathy photo screening pathways. To be clinically acceptable, such systems must also be able to classify other fundus abnormalities and clinical featur...
Introducing Heuristic Information Into Ant Colony Optimization Algorithm for Identifying Epistasis.
IEEE/ACM transactions on computational biology and bioinformatics
Nov 5, 2018
Epistasis learning, which is aimed at detecting associations between multiple Single Nucleotide Polymorphisms (SNPs) and complex diseases, has gained increasing attention in genome wide association studies. Although much work has been done on mapping...
Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data.
IEEE transactions on medical imaging
Oct 22, 2018
The identification and quantification of markers in medical images is critical for diagnosis, prognosis, and disease management. Supervised machine learning enables the detection and exploitation of findings that are known a priori after annotation o...
The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
Medical & biological engineering & computing
Oct 22, 2018
Recently, researchers have built new deep learning (DL) models using a single image modality to diagnose age-related macular degeneration (AMD). Retinal fundus and optical coherence tomography (OCT) images in clinical settings are the most important ...
Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.
Scientific reports
May 21, 2018
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...
A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.
Ophthalmology
Apr 10, 2018
PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these...
Supervised learning and dimension reduction techniques for quantification of retinal fluid in optical coherence tomography images.
Eye (London, England)
Apr 21, 2017
PurposeThe purpose of the present study is to develop fast automated quantification of retinal fluid in optical coherence tomography (OCT) image sets.MethodsWe developed an image analysis pipeline tailored towards OCT images that consists of five ste...
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