Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images

Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images

Finetuning pre-trained deep neural networks (DNN) delicately designed for large-scale natural images may not be suitable for medical images due to the intrinsic difference between the datasets. We propose a strategy to modify DNNs, which improves their performance on retinal optical coherence tomogr...

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Bibliographic Details
Main Authors: Qingge Ji, Jie Huang, Wenjie He, Yankui Sun
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Algorithms
Subjects:
optical coherence tomography
ophthalmology
maculopathy
convolutional neural network
transfer learning
image classification
Online Access:https://www.mdpi.com/1999-4893/12/3/51

Internet

https://www.mdpi.com/1999-4893/12/3/51

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