AIMC Topic: Retina
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Active Cell Appearance Model Induced Generative Adversarial Networks for Annotation-Efficient Cell Segmentation and Identification on Adaptive Optics Retinal Images.
IEEE transactions on medical imaging
Sep 30, 2021
Data annotation is a fundamental precursor for establishing large training sets to effectively apply deep learning methods to medical image analysis. For cell segmentation, obtaining high quality annotations is an expensive process that usually requi...
Imaging depth adaptive resolution enhancement for optical coherence tomography via deep neural network with external attention.
Physics in medicine and biology
Sep 24, 2021
Optical coherence tomography (OCT) is a promising non-invasive imaging technique that owns many biomedical applications. In this paper, a deep neural network is proposed for enhancing the spatial resolution of OCTimages. Different from the previous r...
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.
The Lancet. Digital health
Sep 8, 2021
BACKGROUND: Geographic atrophy is a major vision-threatening manifestation of age-related macular degeneration, one of the leading causes of blindness globally. Geographic atrophy has no proven treatment or method for easy detection. Rapid, reliable,...
Attention-based deep learning system for automated diagnoses of age-related macular degeneration in optical coherence tomography images.
Medical physics
Aug 9, 2021
PURPOSE: The progression of age-related macular degeneration (AMD) is critical to treatment decisions in clinical practice. The disease can be classified into four categories namely, drusen, inactive choroidal neovascularization (CNV), active CNV, an...
Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy.
Computers in biology and medicine
Aug 4, 2021
BACKGROUND: In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate estimation of multi-class retinal fluid (MRF) is required for the activity prescription and intravitreal dose. This study proposes an end-to-end deep learning-bas...
Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images.
The British journal of ophthalmology
Aug 3, 2021
AIMS: Automated machine learning (AutoML) is a novel tool in artificial intelligence (AI). This study assessed the discriminative performance of AutoML in differentiating retinal vein occlusion (RVO), retinitis pigmentosa (RP) and retinal detachment ...
Automated detection of retinal exudates and drusen in ultra-widefield fundus images based on deep learning.
Eye (London, England)
Aug 3, 2021
BACKGROUND: Retinal exudates and/or drusen (RED) can be signs of many fundus diseases that can lead to irreversible vision loss. Early detection and treatment of these diseases are critical for improving vision prognosis. However, manual RED screenin...
Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.
PloS one
Jul 27, 2021
An efficient automatic decision support system for detection of retinal disorders is important and is the need of the hour. Optical Coherence Tomography (OCT) is the current imaging modality for the early detection of retinal disorders non-invasively...
Automatic detection of papilledema through fundus retinal images using deep learning.
Microscopy research and technique
Jul 8, 2021
Papilledema is a syndrome of the retina in which retinal optic nerve is inflated by elevation of intracranial pressure. The papilledema abnormalities such as retinal nerve fiber layer (RNFL) opacification may lead to blindness. These abnormalities co...
Assistive Framework for Automatic Detection of All the Zones in Retinopathy of Prematurity Using Deep Learning.
Journal of digital imaging
Jul 8, 2021
Retinopathy of prematurity (ROP) is a potentially blinding disorder seen in low birth weight preterm infants. In India, the burden of ROP is high, with nearly 200,000 premature infants at risk. Early detection through screening and treatment can prev...
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