AIMC Topic: Retinal Diseases
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Weakly Supervised Lesion Detection From Fundus Images.
IEEE transactions on medical imaging
Dec 6, 2018
Early diagnosis and continuous monitoring of patients suffering from eye diseases have been major concerns in the computer-aided detection techniques. Detecting one or several specific types of retinal lesions has made a significant breakthrough in c...
A novel retinal vessel detection approach based on multiple deep convolution neural networks.
Computer methods and programs in biomedicine
Oct 30, 2018
BACKGROUND AND OBJECTIVE: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detec...
Multilayered Deep Structure Tensor Delaunay Triangulation and Morphing Based Automated Diagnosis and 3D Presentation of Human Macula.
Journal of medical systems
Oct 4, 2018
Maculopathy is the group of diseases that affects central vision of a person and they are often associated with diabetes. Many researchers reported automated diagnosis of maculopathy from optical coherence tomography (OCT) images. However, to the bes...
Clinically applicable deep learning for diagnosis and referral in retinal disease.
Nature medicine
Aug 13, 2018
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common disease...
Artificial intelligence in retina.
Progress in retinal and eye research
Aug 1, 2018
Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in a comprehe...
Automated Layer Segmentation of Retinal Optical Coherence Tomography Images Using a Deep Feature Enhanced Structured Random Forests Classifier.
IEEE journal of biomedical and health informatics
Jul 16, 2018
Optical coherence tomography (OCT) is a high-resolution and noninvasive imaging modality that has become one of the most prevalent techniques for ophthalmic diagnosis. Retinal layer segmentation is very crucial for doctors to diagnose and study retin...
Structure-Preserving Guided Retinal Image Filtering and Its Application for Optic Disk Analysis.
IEEE transactions on medical imaging
May 21, 2018
Retinal fundus photographs have been used in the diagnosis of many ocular diseases such as glaucoma, pathological myopia, age-related macular degeneration, and diabetic retinopathy. With the development of computer science, computer aided diagnosis h...
Antiproliferative and anti-apoptotic effect of astaxanthin in an oxygen-induced retinopathy mouse model.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Apr 11, 2018
OBJECTIVE: To evaluate the impact of intravitreal (IV) and intraperitoneal (IP) astaxanthin (AST) injections on neovascular development (ND), retinal morphology, and apoptotic activity in a C57BL/6J mouse model with hyperoxia-induced retinopathy (HIR...
Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.
IEEE journal of biomedical and health informatics
Feb 28, 2018
Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic diagnosis, near-histological visualization, and quantification of retinal abnormalities such as cysts, exudates, retinal layer disorganization, etc. Int...
Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks.
IEEE journal of biomedical and health informatics
Feb 12, 2018
Optical Coherence Tomography (OCT) is beco-ming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the number of acquired OCT volumes increases, automating the OCT image analysis is becoming increasingly r...
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