The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection

Qiu, Hao1,2; Gu, Zaiwang3; Mou, Lei2; Mao, Xiaoqian2; Fang, Liyang2; Zhao, Yitian2; Liu, Jiang3; Cheng, Jun2

10.1007/978-3-030-32956-3_13

2019

16113349

6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging Computing and Computer-Assisted Intervention, MICCAI 2019

11855 LNCS

104-111

Shenzhen, China

Springer

The optic disc segmentation is an important step for retinal image based disease diagnosis such as glaucoma. The inner limiting membrane (ILM) is the first boundary in the OCT, which can help to extract the retinal pigment epithelium (RPE) through gradient edge information to locate the boundary of the optic disc. Thus, the ILM layer segmentation is of great importance for optic disc localization. In this paper, we build a new optic disc centered dataset from 20 volunteers and manually annotated the ILM boundary in each OCT scan as ground-truth. We also propose a channel attention based context encoder network modified from the CE-Net [1] to segment the optic disc. It mainly contains three phases: the encoder module, the channel attention based context encoder module, and the decoder module. Finally, we demonstrate that our proposed method achieves state-of-the-art disc segmentation performance on our dataset mentioned above.
© Springer Nature Switzerland AG 2019.

其他

EI ; CPCI-S

20194807769141

Aldehydes ; Channel coding ; Computer aided analysis ; Diagnosis ; Image analysis ; Image segmentation ; Medical imaging ; Ophthalmology

Medicine and Pharmacology:461.6 ; Information Theory and Signal Processing:716.1 ; Computer Applications:723.5 ; Imaging Techniques:746 ; Organic Compounds:804.1

EV Compendex

1.School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
2.Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, Ningbo, China
3.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Qiu, Hao,Gu, Zaiwang,Mou, Lei,et al. The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection[C]:Springer,2019:104-111.