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An efficient microaneurysms detection approach in retinal fundus images

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Abstract

Diabetic retinopathy (DR) is one of the retinal disorders and the leading cause of blindness worldwide. Microaneurysms (MA) is the first clinical indication of DR, and the detection of MA helps in early diagnosis. The retinal fundus image analysis helps screen DR through MA detection. In general, the MA detection method consists of preprocessing, enhancement, and classification stages. Preprocessing is crucial to improve the retinal features and reduce the imaging artifacts. Reducing these artifacts is one of the challenging research problems in retinal fundus image analysis. In this paper, a novel improved Non-Local Mean filter (INLMF) is proposed to remove the imaging artifacts. The proposed method is tested on publicly available databases and images collected from Hospital. The proposed method has achieved the best performance metric than the state-of-the-art. The computational time per image is 6.2 sec which is less than other methods.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work is supported by Science and Engineering Research Board (SERB), Department of Science and Technology, Government of INDIA under the sanctioned project file number SRG/2020/000617. The authors acknowledge NVIDIA Corporation, USA for providing GPU under Academic Research Grant scheme.

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Author notes

  1. N. Jagan Mohan, R. Murugan, Tripti Goel, M. Tanveer and Parthapratim Roy are contributed equally to this work.

Authors and Affiliations

  1. Bio-Medical Imaging Laboratory, National Institute of Technology Silchar, Silchar, 788010, Assam, India

    N. Jagan Mohan, R. Murugan & Tripti Goel

  2. Department of Mathematics, Indian Institute of Technology Indore, Indore, 453552, Madhya Pradesh, India

    M. Tanveer

  3. Department of Ophthalomology, Silchar Medical College and Hospital, Silchar, 788014, Assam, India

    Parthapratim Roy

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  1. N. Jagan Mohan
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  4. M. Tanveer
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Correspondence to R. Murugan.

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Mohan, N.J., Murugan, R., Goel, T. et al. An efficient microaneurysms detection approach in retinal fundus images. Int. J. Mach. Learn. & Cyber. 14, 1235–1252 (2023). https://doi.org/10.1007/s13042-022-01696-3

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