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Optic disc detection based on fully convolutional network and weighted matrix recovery model

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Abstract

Eye diseases often affect human health. Accurate detection of the optic disc contour is one of the important steps in diagnosing and treating eye diseases. However, the structure of fundus images is complex, and the optic disc region is often disturbed by blood vessels. Considering that the optic disc is usually a saliency region in fundus images, we propose a weakly-supervised optic disc detection method based on the fully convolution neural network (FCN) combined with the weighted low-rank matrix recovery model (WLRR). Firstly, we extract the low-level features of the fundus image and cluster the pixels using the Simple Linear Iterative Clustering (SLIC) algorithm to generate the feature matrix. Secondly, the top-down semantic prior information provided by FCN and bottom-up background prior information of the optic disc region are used to jointly construct the prior information weighting matrix, which more accurately guides the decomposition of the feature matrix into a sparse matrix representing the optic disc and a low-rank matrix representing the background. Experimental results on the DRISHTI-GS dataset and IDRiD dataset show that our method can segment the optic disc region accurately, and its performance is better than existing weakly-supervised optic disc segmentation methods.

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Funding

This work was supported in part by the National Natural Science Foundation of China under Grant nos. U20A20197, 61973063, Liaoning Key Research and Development Project 2020JH2/10100040, Natural Science Foundation of Liaoning Province 2021-KF-12-01 and the Foundation of National Key Laboratory OEIP-O-202005.

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Authors and Affiliations

  1. Faculty of Robot Science and Engineering, Northeastern University, 110170, Shen Yang, Liao Ning, China

    Siqi Wang, Xiaosheng Yu, Jianning Chi, Pengfei Lv, Junxiang Wang & Chengdong Wu

  2. Art School, HE University, 110163, Shen Yang, Liao Ning, China

    Wenzhuo Jia

  3. Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education, Northeastern University, 110170, Shen Yang, Liao Ning, China

    Jianning Chi

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  1. Siqi Wang
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Correspondence to Xiaosheng Yu.

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Xiaosheng Yu and Chengdong Wu contributed equally to this work.

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Wang, S., Yu, X., Jia, W. et al. Optic disc detection based on fully convolutional network and weighted matrix recovery model. Med Biol Eng Comput 61, 3319–3333 (2023). https://doi.org/10.1007/s11517-023-02891-2

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