A Generative Model for OCT Retinal Layer Segmentation by Groupwise Curve Alignment

Wenjun Duan, Yuanjie Zheng, Yanhui Ding, Sujuan Hou, Yufang Tang, Yan Xu, Maoling Qin, Jianfeng Wu, Dinggang Shen, Hongsheng Bi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Retinal layer segmentation from optical coherence tomography (OCT) is of fundamental importance for measuring retinal layer thicknesses. These thickness measurements have been shown to correlate well with the severity of different ocular diseases; hence, they provide useful diagnostic information concerning diseases. Manual segmentation of retinal layers from OCT remains dominant in ophthalmological clinical practice but has serious drawbacks: it is time consuming, labor intensive, and results in inter/intra-rater variations. Computer aided segmentation has attracted intensive research attention because it holds the potential not only to provide repeatable, quantitative, and objective results but also to reduce the time and effort required to delineate the retinal layers. However, most of the existing computer based retinal layer segmentation techniques focus on segmenting specific layers by exploring their unique characteristics; thus, they can fail to segment a retinal layer that is totally different. In this paper, we propose a generative retinal layer segmentation method based on groupwise curve alignment that combines the capabilities of segmenting different retinal layers into a unified framework. This method is unique for both its accuracy and its ability to segment any retinal layer without any special modifications. We experimentally validate that the proposed method outperforms a representative state-of-the-art technique by using images of both normal healthy eyes and diseased eyes. Our method is potentially useful in a large variety of practical applications involving retinal layer segmentation from OCT.

Original languageEnglish
Pages (from-to)25130-25141
Number of pages12
JournalIEEE Access
Publication statusPublished - 2018 Apr 16

Bibliographical note

Publisher Copyright:
© 2013 IEEE.


  • Optical coherence tomography (OCT)
  • dynamic time warping
  • joint curve matching
  • retinal layer segmentation

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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