Deep Learning-Based Diagnosis of Retinal Diseases Using OCT
The implementation of deep learning model used to detect four types of retinal cases
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There are numerous eye conditions but the most two common retinal conditions are Age- Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and aged, there are two types ofAMD are wet AMD (Choroidal neovascularization (CNV)) and dry AMD (DRUSEN).Diabetic Macular Edema (DME), which is a complication of diabetes that can affect the fovea and it caused by fluid accumulation in the macula. thus, early discovery of conditions is a critical significance. The goal of this thesis is implementation of deep learning model used to detec...
There are numerous eye conditions but the most two common retinal conditions are Age- Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and aged, there are two types ofAMD are wet AMD (Choroidal neovascularization (CNV)) and dry AMD (DRUSEN).Diabetic Macular Edema (DME), which is a complication of diabetes that can affect the fovea and it caused by fluid accumulation in the macula. thus, early discovery of conditions is a critical significance. The goal of this thesis is implementation of deep learning model used to detect four types of retinal cases (NORMAL, CNV, DME, and DRUSEN) by using Convolutional Neural Network (CNN) to Avoid manual diagnostic errors and help doctors make faster, and more accurate diagnoses.
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