BACKGROUND: To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD).
PURPOSE: The purpose of this study was to predict low and high anti-VEGF injection requirements during a pro re nata (PRN) treatment, based on sets of optical coherence tomography (OCT) images acquired during the initiation phase in neovascular AMD.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
31946057
Development of an automated sub-retinal fluid segmentation technique from optical coherence tomography (OCT) scans is faced with challenges such as noise and motion artifacts present in OCT images, variation in size, shape and location of fluid pocke...
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
PURPOSE: To evaluate the performance of retinal specialists in detecting retinal fluid presence in spectral domain OCT (SD-OCT) scans from eyes with age-related macular degeneration (AMD) and compare performance with an artificial intelligence algori...
PURPOSE: Subretinal injections of therapeutics are commonly used to treat ocular diseases. Accurate dosing of therapeutics at target locations is crucial but difficult to achieve using subretinal injections due to leakage, and there is no method avai...
IMPORTANCE: Large amounts of optical coherence tomographic (OCT) data of diabetic macular edema (DME) are acquired, but many morphologic features have yet to be identified and quantified.