Min-Cut Segmentation of Retinal OCT Images

  • Bashir Isa DodoEmail author
  • Yongmin Li
  • Khalid Eltayef
  • Xiaohui Liu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1024)


Optical Coherence Tomography (OCT) is one of the most vital tools for diagnosing and tracking progress of medication of various retinal disorders. Many methods have been proposed to aid with the analysis of retinal images due to the intricacy of retinal structures, the tediousness of manual segmentation and variation from different specialists. However image artifacts, in addition to inhomogeneity in pathological structures, remain a challenge, with negative influence on the performance of segmentation algorithms. In this paper we present an automatic retinal layer segmentation method, which comprises of fuzzy histogram hyperbolization and graph cut methods. We impose hard constraints to limit search region to sequentially segment 8 boundaries and 7 layers of the retina on 150 OCT B-Sans images, 50 each from the temporal, nasal and center of foveal regions. Our method shows positive results, with additional tolerance and adaptability to contour variance and pathological inconsistence of the retinal structures in all regions.


Retinal layer segmentation Optical Coherence Tomography Graph-cut Image analysis 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bashir Isa Dodo
    • 1
    Email author
  • Yongmin Li
    • 1
  • Khalid Eltayef
    • 1
  • Xiaohui Liu
    • 1
  1. 1.Brunel University LondonLondonUK

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