Retinal Vessel Segmetation

Rui Xu¹, Xinchen Ye¹

¹ Dalian University of Technology

Abstract

Recently, the joint research team of Dalian University of Technology (DUT) and Risumeikan University (RU) has made important progress in the field of retinal vessel segmentation. Their paper “Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network” was accepted by Medical Image Computing and Computer Assisted Intervention Society (MICCAI), which is an international top academic corporation in the field of medical image analysis. This research result was jointly completed by DUT Associate Prof. Xu Rui, Associate Prof. Ye Xinchen, Graduate Student Liu Tiantian, and RU Prof. Chen Yanwei from College of Information Science and Engineering. In addition, it was funded by the DUT - RU Co-Research Center of Advanced ICT for Active Life.

Many deep learning based methods have been proposed for retinal vessel segmentation, however few of them focus on the connectivity of segmented vessels, which is quite important for a practical computer-aided diagnosis system on retinal images. In the paper, the research team proposes an efficient network to address this problem. A U-shape network is enhanced by introducing a semantics-guided module, which integrates the enriched semantics information to shallow layers for guiding the network to explore more powerful features. Besides, a recursive refinement iteratively applies the same network over the previous segmentation results for progressively boosting the performance while increasing no extra network parameters. The carefully designed recursive semantics-guided network has been extensively evaluated on several public datasets. Experimental results have shown the efficiency of the proposed method.

Related Research Results of Retinal Vessel Segmentation:

[1] Rui Xu, Guiliang Jiang, Xinchen Ye*, Yen-Wei Chen, Retinal Vessel Segmentation via Multiscaled Deep Guidance, Pacific Rim Conference on Multimedia 2018 (PCM 2018), Hefei, China, September 21-22, 2018.

[2] Rui Xu, Xinchen Ye*, Guiliang Jiang, Tiantian Liu, Liang Li, Satoshi Tanaka, Retinal Vessel Segmentation via a Semantics and Multi-Scale Aggregation Network, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Virtual Barcelona, May 4-8, 2020.

[3] Rui Xu, Tiantian Liu, Xinchen Ye*, Yen-Wei Chen, Boosting Connectivity in Retinal Vessel Segmentation via a Recursive Semantics-Guided Network, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020), accepted.  (arXiv Version : https://arxiv.org/abs/2004.12776)

[4] Rui Xu, Tiantian Liu, Xinchen Ye*, Fei Liu, Lin Lin, Liang Li, Satoshi Tanaka, Yen Wei Chen, Joint Extraction of Retinal Vessels and Centerlines Based on Deep Semantics and Multi-Scaled Cross-Task Aggregation, IEEE Journal of Biomedical and Health Informatics, 10.1109/JBHI.2020.3044957, 2021 （中科院1区TOP）

DUT - RU Co-Research Center of Advanced ICT for Active Life

It was established on the development zone campus of DUT in June, 2018. It is an achievement of international cooperation between DUT and RU and mainly conducted by DUT-RU International School of Information Science & Engineering. The Co-Research Center has set up a platform for international research cooperation and communication in the cross research field of health care and information science, and established the “International Research Exchange and Cooperation Promotion Project”, which funds relevant researchers to carry out in-depth international research cooperation in ICT (information computing technology), medical and health fields.