Automated Diabetic Macular Edema (DME) analysis using fine tuning with inception-resnet-v2 on oct images

• Main Authors: Kamble, R.M., Kokare, M., Chan, G.C.Y., Perdomo, O., González, F.A., Müller, H., Mériaudeau, F.
• Format: Conference or Workshop Item
• Published: Institute of Electrical and Electronics Engineers Inc. 2019
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062772479&doi=10.1109%2fIECBES.2018.8626616&partnerID=40&md5=5afcb4ca34c7fd4c0676b9c468644f97; http://eprints.utp.edu.my/23655/

Accurate detection of diabetic macular edema (DME) is an important task in optical coherence tomography (OCT) images of the eye. A relatively simple and practical approach is proposed in this paper. A pre-trained convolutional neural network (CNN) is fine tuned for a classification of DME versus nor...