A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography [PDF]
Purpose - To develop and validate a deep learning (DL) framework for the detection and quantification of drusen and reticular pseudodrusen (RPD) on optical coherence tomography scans. Design - Development and validation of deep learning models for classification and feature segmentation.
R. Schwartz+14 more
arxiv +3 more sources
Age‐related macular degeneration (AMD) is a leading cause of blindness worldwide. Drusen are key contributors to the etiology of AMD and the ability to modulate drusen biogenesis could lead to therapeutic strategies to slow or halt AMD progression.
Miguel Flores‐Bellver+17 more
doaj +2 more sources
Drusen are hallmarks of early and intermediate age-related macular degeneration (AMD) but their quantification remains a challenge. We compared automated drusen volume measurements between different OCT devices.
Davide Garzone+12 more
doaj +2 more sources
Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography [PDF]
Automated drusen segmentation in retinal optical coherence tomography (OCT) scans is relevant for understanding age-related macular degeneration (AMD) risk and progression. This task is usually performed by segmenting the top/bottom anatomical interfaces that define drusen, the outer boundary of the retinal pigment epithelium (OBRPE) and the Bruch's ...
Rhona Asgari+6 more
arxiv +3 more sources
Association of soft drusen with risk of all-cause and specific-cause mortality in the National Health and Nutrition Examination Survey, 2005 to 2008 [PDF]
The aim of this study is to investigate the correlation between soft drusen and the likelihood of mortality from all causes and specific ailments within a representative United States population.
Huihui Wu+7 more
doaj +2 more sources
U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography [PDF]
The presence of drusen is the main hallmark of early/intermediate age-related macular degeneration (AMD). Therefore, automated drusen segmentation is an important step in image-guided management of AMD. There are two common approaches to drusen segmentation. In the first, the drusen are segmented directly as a binary classification task.
Rhona Asgari+5 more
arxiv +2 more sources
Drusen are known to be the important hallmark to predict the development of age-related macular degeneration (AMD). The prevalence of drusen is lower in Asians compared with Caucasians so that the role of signs constituting early AMD is not well ...
Shoji Notomi+10 more
doaj +2 more sources
Developing an image-based grading scale for peripheral drusen to investigate associations of peripheral drusen type with age-related macular degeneration [PDF]
Age-related macular degeneration (AMD) is a leading cause of blindness. It is associated with peripheral drusen which has not been categorized. We investigated peripheral drusen to validate an image grading system and to understand possible associations ...
Paripoorna Sharma+4 more
doaj +2 more sources
Automatic Classification of Bright Retinal Lesions via Deep Network Features [PDF]
The diabetic retinopathy is timely diagonalized through color eye fundus images by experienced ophthalmologists, in order to recognize potential retinal features and identify early-blindness cases. In this paper, it is proposed to extract deep features from the last fully-connected layer of, four different, pre-trained convolutional neural networks ...
Elawady, Mohamed+2 more
arxiv +2 more sources
Automated segmentation and quantification of calcified drusen in 3D swept source OCT imaging.
Qualitative and quantitative assessments of calcified drusen are clinically important for determining the risk of disease progression in age-related macular degeneration (AMD).
Jie Lu+13 more
semanticscholar +1 more source