Corneal Endothelial Cell Segmentation with Multiple Long-range Dependencies

Zeng, Lingxi1,2; Zhang, Yinglin1,2,3; Higashita, Risa1,2,3,4; Liu, Jiang1,2,3

10.1145/3637732.3637778

2023

10th International Conference on Biomedical and Bioinformatics Engineering (ICBBE)

2023 10TH INTERNATIONAL CONFERENCE ON BIOMEDICAL AND BIOINFORMATICS ENGINEERING, ICBBE 2023

NOV 09-12, 2023

Ritsumeikan Univ,Kyoto,JAPAN

1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES

ASSOC COMPUTING MACHINERY

Corneal endothelial cell segmentation is an important task in ophthalmology, but it is challenging due to variations in image characteristics across different datasets. Existing deep learning methods have limitations in capturing long-range dependencies that are critical for accurate segmentation. To address this issue, we propose a novel multiple long-range dependencies network (MLD-Net) that effectively incorporates different types of long-range dependency information to achieve robust segmentation across datasets. The network employs dilated convolutions and attention gates to capture spatial and layer-level dependencies, respectively. The entire network is densely connected, facilitating the sharing of long-range dependency information across multiple scales. We demonstrate the effectiveness of MLD-Net on four different corneal endothelium microscope image datasets: SREP, BiolmLab, Rodrep, and TM-EM3000. Our experimental results show that MLD-Net outperforms existing state-of-the-art methods, achieving robustness and high accuracy in corneal endothelial cell segmentation.

Segmentation Deep Learning Long-range Dependency Corneal Endothelial Cell

第一 ; 通讯

英语

CPCI-S

General Program of National Natural Science Foundation of China[82272086] ; Guangdong Provincial Department of Education[2020ZDZX3043] ; Shenzhen Natural Science Fund["JCYJ20200109140820699","20200925174052004"]

Computer Science ; Engineering ; Radiology, Nuclear Medicine & Medical Imaging

Computer Science, Artificial Intelligence ; Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging

WOS:001180685400009

Web of Science

1.Southern Univ Sci & Technol, Res Inst Trustworthy Autonomous Syst, Shenzhen, Guangdong, Peoples R China
2.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Guangdong, Peoples R China
3.Univ Nottingham Ningbo China, China Sch Comp Sci, Ningbo, Zhejiang, Peoples R China
4.Tomey Corp, Nagoya, Aichi, Japan

Zeng, Lingxi,Zhang, Yinglin,Higashita, Risa,et al. Corneal Endothelial Cell Segmentation with Multiple Long-range Dependencies[C]. 1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES:ASSOC COMPUTING MACHINERY,2023.