期刊论文

Zhao, GZ;Chen, XD

英文

Journal of Visual Communication and Image Representation

1047-3203

2019

59

Feb.

327-333

10.1016/j.jvcir.2019.01.022

This work was supported in part by the National Natural Science Foundation under Grant No. 61771192 , 61471167 , and 61462089 , the National Natural Science Foundation for Young Scientist of China under Grant No. 61501180 , China Postdoctoral Science Foundation funded Project No. 2017T100597 , and National Natural Science Foundation of Hunan Province Grant No. 2018JJ3077 . This work was supported in part by the National Natural Science Foundation under Grant No. 61771192, 61471167, and 61462089, the National Natural Science Foundation for Young Scientist of China under Grant No. 61501180, China Postdoctoral Science Foundation funded Project No. 2017T100597, and National Natural Science Foundation of Hunan Province Grant No. 2018JJ3077.

本校为通讯机构

Optical coherence tomography (OCT) can achieve the high-resolution 3D tomography imaging of the retina, which is crucial for the diagnosis of retinal diseases. Currently, the classification of retinal OCT images is mainly conducted by ophthalmologists, which is time consuming and subjective. In this paper, we propose an iterative fusion convolutional neural network (IFCNN) method for the automatic classification of retinal OCT image. In the convolutional neural network (CNN), different convolutional layers contain feature information from different scales. Therefore, the proposed network adopt...