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Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm

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Abstract

Image segmentation plays an important role in the analysis of retinal images as the extraction of the optic disk provides important cues for accurate diagnosis of various retinopathic diseases. In recent years, gradient vector flow (GVF) based algorithms have been used successfully to successfully segment a variety of medical imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods can lead to less accurate segmentation results in certain cases. In this paper, we propose the use of a new mean shift-based GVF segmentation algorithm that drives the internal/external energies towards the correct direction. The proposed method incorporates a mean shift operation within the standard GVF cost function to arrive at a more accurate segmentation. Experimental results on a large dataset of retinal images demonstrate that the presented method optimally detects the border of the optic disc.

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Authors and Affiliations

  1. The Institute of Electronics, Communications and Information Technology (ECIT), Queen’s University Belfast, Belfast, BT3 9DT, UK

    Huiyu Zhou

  2. Department of Computer Science, Loughborough University, Loughborough, LE11 3TU, UK

    Gerald Schaefer

  3. Guangxi Medical University, Nanning, 530027, Peoples’ Republic of China

    Tangwei Liu & Faquan Lin

Authors
  1. Huiyu Zhou
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  2. Gerald Schaefer
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  3. Tangwei Liu
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  4. Faquan Lin
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Correspondence to Huiyu Zhou.

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Zhou, H., Schaefer, G., Liu, T. et al. Segmentation of optic disc in retinal images using an improved gradient vector flow algorithm. Multimed Tools Appl 49, 447–462 (2010). https://doi.org/10.1007/s11042-009-0443-0

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