AI Medical Compendium Topic:
Tomography, Optical Coherence

Clear Filters Showing 761 to 770 of 778 articles

Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD.

Journal of digital imaging
Age-related macular degeneration (ARMD) is one of the most common retinal syndromes that occurs in elderly people. Different eye testing techniques such as fundus photography and optical coherence tomography (OCT) are used to clinically examine the A...

Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence.

Investigative ophthalmology & visual science
PURPOSE: While millions of individuals show early age-related macular degeneration (AMD) signs, yet have excellent vision, the risk of progression to advanced AMD with legal blindness is highly variable. We suggest means of artificial intelligence to...

Fusing Results of Several Deep Learning Architectures for Automatic Classification of Normal and Diabetic Macular Edema in Optical Coherence Tomography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Diabetic Macular Edema (DME) is a severe eye disease that can lead to irreversible blindness if it is left untreated. DME diagnosis still relies on manual evaluation from opthalmologists, thus the process is time consuming and diagnosis may be subjec...

Lumen Segmentation in Optical Coherence Tomography Images using Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lumen segmentation in Optical Coherence Tomography (OCT) images is a very important step to analyze points of interest that may help on atherosclerosis diagnostic and treatment. Past studies use many different methods to segment the lumen in IVOCT im...

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Investigative ophthalmology & visual science
PURPOSE: To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progres...

Macular OCT Classification Using a Multi-Scale Convolutional Neural Network Ensemble.

IEEE transactions on medical imaging
Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) imaging technique, a CAD system in retinal OCT is essential to assist op...

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

Cell
The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common t...

A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head.

Investigative ophthalmology & visual science
PURPOSE: To develop a deep learning approach to digitally stain optical coherence tomography (OCT) images of the optic nerve head (ONH).

Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.

Journal of biomedical optics
Intravascular optical coherence tomography (OCT) is an optical imaging modality commonly used in the assessment of coronary artery diseases during percutaneous coronary intervention. Manual segmentation to assess luminal stenosis from OCT pullback sc...