计算机科学 ›› 2015, Vol. 42 ›› Issue (9): 272-277.doi: 10.11896/j.issn.1002-137X.2015.09.053

• 图形图像与模式识别 • 上一篇    下一篇

应用多尺度三维图搜索的SD-OCT图像层分割方法

牛四杰,陈强,陆圣陶,沈宏烈   

  1. 南京理工大学计算机科学与工程学院 南京210094,南京理工大学计算机科学与工程学院 南京210094,南京理工大学计算机科学与工程学院 南京210094,南京理工大学计算机科学与工程学院 南京210094
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受青蓝工程(D040201),中央高校基本科研业务费专项资金(30920140111004)资助

SD-OCT Image Layer Segmentation Using Multi-scale 3-D Graph Search Method

NIU Si-jie, CHEN Qiang, LU Sheng-tao and SHEN Hong-lie   

  • Online:2018-11-14 Published:2018-11-14

摘要: 频谱域光学相干层析技术(SD-OCT)是一种广泛应用于眼科领域的成像技术,视网膜组织层分割对视网膜疾病诊断起着至关重要的作用。传统的三维图搜索方法能够同时分割k(k≥1)个三维面,但其存在时间复杂度高、分割病变图像鲁棒性弱等问题。在传统三维图搜索模型的基础上引入多尺度思想,提出应用多尺度三维图搜索的SD-OCT视网膜图像分割方法。首先根据每个组织层的特点,为每层构造一个合理的顶点权重;然后利用相邻列的最大与最小高度差构造列约束限制,改进表面的平滑约束条件;最后利用低尺度的图像,应用三维图搜索方法进行粗分割,逐步向高一尺度应用三维图搜索方法进行单表面细分割。使用改进算法对3组正常眼睛及1组老年黄斑变性视网膜图像进行分割,并将结果与手动分割及传统三维图搜索方法进行比较,实验结果表明,改进算法能够准确有效地分割出3个层边界(边界位置绝对误差是3.86±2.50μm),并且接近于手动分割结果(3.78±2.76μm),优于传统三维图搜索方法(7.92±3.31μm)。

关键词: SD-OCT技术,视网膜图像分割,多尺度,三维图搜索

Abstract: Spectral domain optical coherence tomography (SD-OCT) imaging technique is widely used in the field of ophthalmology.The segmentation of retinal tissue layers plays a vital role in the diagnosis of retinal disease.The traditional 3-D graph search method is able to segment k surfaces simultaneously.Problems of this algorithm associated with high time complexity and weak robustness of segmenting pathological retinal images have limited its utility.Multi-scale theory was introduced to the traditional 3-D graph search modal,and a 3-D graph search algorithm based on multi-scale for segmenting retinal images was proposed in this paper.Firstly,reasonable cost functions are constructed for each surface according to the characteristics of the layer.Then the minimum and maximum differences in height of adjacent columns are utilized to construct inter-column constraints to improve smoothness constraints of surfaces.Finally,3-D graph search method is used for coarse segmentation of lower-scale images and then a search region of higher-scale images is redefined for a more accurate result.The improved algorithm was evaluated on 3 groups of normal eyes and 1 group of abnormal eye with age-related macular degeneration.The experimental results were compared with manual segmentation and traditional 3-D graph search method.The results demonstrate that the improved method can effectively detect 3 layer surfaces (the mean absolute boundary positioning difference is 3.86±2.50μm) more closely to manual segmentation (3.78±2.76μm),and it is better than traditional 3-D graph search method (7.92±3.31μm).

Key words: Spectral domain optical coherence tomography,Retinal image segmentation,Multi-scale,3-D graph search

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