Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low Contrast Sclerocho-roidal Junction Using Deep Learning

This project aims to calculate Choroid Vascularity Index (CVI) in optical coherenece tomography (OCT) images, using loss modified U-Net. The method is detailed in "Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images low contrast sclerochoroidal junction Using Deep Learning". The dataset consists of Enhanced-depth imaging optical coherence tomography images from two patient groups. • First dataset is including Raster OCT B-scans from patients with diabetic retinopathy. • Second dataset is including EDI-HD OCT B-scans from patients with pachychoroid spectrum.

Please site the following paper if you used this dataset: Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images low contrast sclerochoroidal junction Using Deep Learning

Related Organizations

Tehran University of Medical Sciences
Iran (Islamic Republic of)
Farabi Eye Hospital
Iran (Islamic Republic of)
Durham University
United Kingdom

Keywords

diabetic retinopathy, pachychoroid spectrum, OCT B-scans

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