Deep Residual Network based Automatic Image Grading for Diabetic Macular Edema

2018-07-01Engineering in Medicine and Biology Society (EMBC), 2018 40th Annual International Conference of the IEEE 2018Code Available0· sign in to hype

Santhosh Kumar Sukumar, Kamalakkannan Ravi, Supriti Mulay, Keerthi Ram, Mohanasankar Sivaprakasam

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Abstract

Diabetic Macular Edema (DME) is an advanced symptom of diabetic retinopathy that affects central vision of diabetes patients. An automated system for early detection of DME symptom has been proposed herein to elude vision impairment and assist in effective treatment. Transfer learning based on Deep Residual Networks (ResNets) which has proven to be a very successful model in many image classification applications and is used in the proposed system for automatic grading of DME images. Validation of the developed system on Indian Diabetic Retinopathy Image Dataset (IDRID 2018) results in 86.56 % detection accuracy.

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Fovea Detection image-classification Image Classification Medical Image Analysis Medical Image Classification Optic Disc Detection Transfer Learning

Deep Residual Network based Automatic Image Grading for Diabetic Macular Edema

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