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Retinal vessel image segmentation algorithm based on encoder-decoder structure

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Abstract

The accurate segmentation of retinal vessel image is significant for the early diagnosis of some diseases. A retinal vessel image segmentation algorithm based on an encoder-decoder structure is proposed. In the encoding section, the Inception module is used, which uses convolution kernels of different scales to achieve features extract to obtain images multi-scale information. So as to enable the model to perceive blood vessels of various shapes and improve the accuracy of segmentation of small blood vessels, multiple pyramid pooling modules are adopted in the decoding process to aggregate more contextual information, and multi-scale and multi-local area feature fusion is used to improve segmentation effect. In addition, the feature fusion method is applied in the upsampling process to fuse low-order semantic features to obtain more low-level detailed information, thereby further promote the segmentation effect. The experimental results on DRIVE and STAER fundus image datasets show that the algorithm has higher sensitivity, accuracy and AUC value compared with other algorithms, and the segmentation effect is better.

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Data availablity

The datasets analysed during the current study are available from the Introduction - Grand Challenge (grand-challenge.org).

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Funding

This work was supported by the National Natural Science Foundation of China under Grant 61502262

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Authors and Affiliations

  1. School of Information and Control Engineering, Qingdao University of Technology, Qingdao, 266520, China

    ZhengLi Zhai, Shu Feng, Luyao Yao & Penghui Li

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  1. ZhengLi Zhai
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  2. Shu Feng
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  3. Luyao Yao
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  4. Penghui Li
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Contributions

All authors designed the research. Material preparation, data collection and analysis were performed by Zhengli Zhai and Shu Feng, these authors contributed equally to this work. The first draft of the manuscript was written by Shu Feng, Luyao Yao and Penghui Li. All authors commented on previous versions of the manuscript and read and approved the final manuscript.”

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Correspondence to ZhengLi Zhai.

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The authors have no relevant financial or non-financial interests to disclose.

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Zhai, Z., Feng, S., Yao, L. et al. Retinal vessel image segmentation algorithm based on encoder-decoder structure. Multimed Tools Appl 81, 33361–33373 (2022). https://doi.org/10.1007/s11042-022-13176-5

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  • DOI: https://doi.org/10.1007/s11042-022-13176-5

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