Oct 25, 2017

Deep tessellated retinal image detection using Convolutional Neural Networks

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Xingzheng Lyu Sanyuan Zhang

Abstract

Tessellation in fundus is not only a visible feature for aged-related and myopic maculopathy but also confuse retinal vessel segmentation. The detection of tessellated images is an inevitable processing in retinal image analysis. In this work, we propose a model using convolutional neural network for detecting tessellated images. The input to the model is pre-processed fundus image, and the output indicate whether this photograph has tessellation or not. A database with 12,000 colour retinal images is collected to evaluate the classification performance. The best tessellation classifier achieves accuracy of 97.73% and AUC value of 0.9659 using pretrained GoogLeNet and transfer learning technique.

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Mentioned in this Paper

Biological Neural Networks
Biologic Segmentation
Classification
Fundus
Congenital Clubfoot
Evaluation
Neural Stem Cells
Neural Network Simulation
Retinaldehyde
Fundus Uteri

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