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

Hao Qiu; Zaiwang Gu; Lei Mou; Xiaoqian Mao; Liyang Fang; Yitian Zhao; Jiang Liu; Jun Cheng

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

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

Hao Qiu
, Zaiwang Gu
, Lei Mou
, Xiaoqian Mao
, Liyang Fang
, Yitian Zhao
, Jiang Liu
, Jun Cheng

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings
Editors	Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
Publisher	Springer
Pages	104-111
Number of pages	8
ISBN (Print)	9783030329556
DOIs	https://doi.org/10.1007/978-3-030-32956-3_13
Publication status	Published - 2019
Externally published	Yes
Event	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 - Shenzhen, China Duration: 17 Oct 2019 → 17 Oct 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11855 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	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
Country/Territory	China
City	Shenzhen
Period	17/10/19 → 17/10/19

Keywords

Channel attention based context encoder
Disc segmentation
ILM layer detection

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

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

Cite this

Qiu, H., Gu, Z., Mou, L., Mao, X., Fang, L., Zhao, Y., Liu, J., & Cheng, J. (2019). The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection. In H. Fu, M. K. Garvin, T. MacGillivray, Y. Xu, & Y. Zheng (Eds.), Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings (pp. 104-111). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11855 LNCS). Springer. https://doi.org/10.1007/978-3-030-32956-3_13

Qiu, Hao ; Gu, Zaiwang ; Mou, Lei et al. / The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection. Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings. editor / Huazhu Fu ; Mona K. Garvin ; Tom MacGillivray ; Yanwu Xu ; Yalin Zheng. Springer, 2019. pp. 104-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{5bdc31cc02324c939e1c6cf0308e85c1,

title = "The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection",

abstract = "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.",

keywords = "Channel attention based context encoder, Disc segmentation, ILM layer detection",

author = "Hao Qiu and Zaiwang Gu and Lei Mou and Xiaoqian Mao and Liyang Fang and Yitian Zhao and Jiang Liu and Jun Cheng",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 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 ; Conference date: 17-10-2019 Through 17-10-2019",

year = "2019",

doi = "10.1007/978-3-030-32956-3\_13",

language = "English",

isbn = "9783030329556",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "104--111",

editor = "Huazhu Fu and Garvin, \{Mona K.\} and Tom MacGillivray and Yanwu Xu and Yalin Zheng",

booktitle = "Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings",

}

Qiu, H, Gu, Z, Mou, L, Mao, X, Fang, L, Zhao, Y, Liu, J & Cheng, J 2019, The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection. in H Fu, MK Garvin, T MacGillivray, Y Xu & Y Zheng (eds), Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11855 LNCS, Springer, pp. 104-111, 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, Shenzhen, China, 17/10/19. https://doi.org/10.1007/978-3-030-32956-3_13

The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection. / Qiu, Hao; Gu, Zaiwang; Mou, Lei et al.
Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings. ed. / Huazhu Fu; Mona K. Garvin; Tom MacGillivray; Yanwu Xu; Yalin Zheng. Springer, 2019. p. 104-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11855 LNCS).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection

AU - Qiu, Hao

AU - Gu, Zaiwang

AU - Mou, Lei

AU - Mao, Xiaoqian

AU - Fang, Liyang

AU - Zhao, Yitian

AU - Liu, Jiang

AU - Cheng, Jun

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Channel attention based context encoder

KW - Disc segmentation

KW - ILM layer detection

UR - https://www.scopus.com/pages/publications/85075678723

U2 - 10.1007/978-3-030-32956-3_13

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

M3 - Conference contribution

AN - SCOPUS:85075678723

SN - 9783030329556

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 104

EP - 111

BT - Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings

A2 - Fu, Huazhu

A2 - Garvin, Mona K.

A2 - MacGillivray, Tom

A2 - Xu, Yanwu

A2 - Zheng, Yalin

PB - Springer

T2 - 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

Y2 - 17 October 2019 through 17 October 2019

ER -

Qiu H, Gu Z, Mou L, Mao X, Fang L, Zhao Y et al. The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection. In Fu H, Garvin MK, MacGillivray T, Xu Y, Zheng Y, editors, Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings. Springer. 2019. p. 104-111. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-32956-3_13

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

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Keywords

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