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

Huiyu Zhou, Gerald Schaefer, Tangwei Liu, Faquan Lin

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)447-462
Number of pages16
JournalMultimedia Tools and Applications
Issue number3
Publication statusPublished - Mar 2010

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software
  • Media Technology


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