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SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation

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Abstract

Since morphology of retinal blood vessels plays a key role in ophthalmological disease diagnosis, retinal vessel segmentation is an indispensable step for the screening and diagnosis of retinal diseases with fundus images. In this paper, deep convolution adversarial network combined with short connection and dense block is proposed to separate blood vessels from fundus image, named SUD-GAN. The generator adopts U-shape encode-decode structure and adds short connection block between convolution layers to prevent gradient dispersion caused by deep convolution network. The discriminator is all composed of convolution block, and dense connection structure is added to the middle part of the convolution network to strengthen the spread of features and enhance the network discrimination ability. The proposed method is evaluated on two publicly available databases, the DRIVE and STARE. The results show that the proposed method outperforms the state-of-the-art performance in sensitivity and specificity, which were 0.8340 and 0.9820, and 0.8334 and 0.9897 respectively on DRIVE and STARE, and can detect more tiny vessels and locate the edge of blood vessels more accurately.

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Funding

The paper supported by key specialized research and development program of Henan Province (202102210170); Applied research plan of key scientific research projects in Henan colleges and Universities(19A510011).

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Authors and Affiliations

  1. Key Laboratory of Grain Information Processing and Control (Henan University of Technology), Ministry of Education, ZhengZhou, 450001, China

    Tiejun Yang

  2. School of Artificial Intelligence and Big Data, Henan University of Technology, ZhengZhou, 450001, China

    Tiejun Yang

  3. College of Information Science and Technology, Henan University of Technology, Zhengzhou, 450001, China

    Tingting Wu, Lei Li & Chunhua Zhu

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  1. Tiejun Yang
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  2. Tingting Wu
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  4. Chunhua Zhu
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Correspondence to Tingting Wu.

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Yang, T., Wu, T., Li, L. et al. SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation. J Digit Imaging 33, 946–957 (2020). https://doi.org/10.1007/s10278-020-00339-9

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  • DOI: https://doi.org/10.1007/s10278-020-00339-9

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