基于随机森林的频谱域光学相干层析技术的图像视网膜神经纤维层分割

陈强; 徐军; 牛四杰

doi:10.11999/JEIT160663

基于随机森林的频谱域光学相干层析技术的图像视网膜神经纤维层分割

doi: 10.11999/JEIT160663

2.
(南京理工大学计算机科学与工程学院南京 210094) ②(福建省信息处理与智能控制重点实验室(闽江学院) 福州 350121) ③(济南大学信息科学与工程学院济南 250022)

基金项目:

国家自然科学基金(61671242)，中央高校基本科研业务费专项资金(30920140111004)，六大人才高峰(2014-SWYY-024)，福建省信息处理与智能控制重点实验室(闽江学院)开放课题基(MJUKF201706)

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出版历程
- 收稿日期: 2016-06-24
- 修回日期: 2017-03-23
- 刊出日期: 2017-05-19

Retinal Nerve Fiber Layer Segmentation of Spectral Domain Optical Coherence Tomography Images Based on Random Forest

2.
(School of Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China)

Funds:

The National Natural Science Foundation of China (61671242), The Special Funds of Fundamental Research for the Central Universities (30920140111004), Six Big Talent Peals (2014-SWYY-024), The Open Fund Project of Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University)(MJUKF201706)

摘要

摘要: 频谱域光学相干层析技术是一种广泛应用于眼科疾病诊断的成像技术，而视网膜层分割对青光眼的诊断有很好的参考价值。该文利用随机森林分类器寻找视网膜层间单像素宽的边界，随机森林分类器由12个特征训练产生，其中相对灰度特征和邻域特征较好地解决灰度不均匀的分割误差大问题。对10组带有青光眼病变的视网膜图像进行分割，并与传统算法和Iowa软件进行比较，平均边界绝对误差为9.202.57 m, 11.332.99 m和10.273.01 m。实验结果表明，改进算法可以较好地分割视网膜神经纤维层。
- 频域光学相干层技术 /
- 青光眼 /
- 视网膜图像分割 /
- 视网膜神经纤维层 /
- 随机森林
Abstract: Spectral Domain Optical Coherence Tomography (SD-OCT) imaging technique is widely used in the diagnosis of ophthalmology diseases. The segmentation of retinal layers plays a very important role in the diagnosis of glaucoma. In this paper, a random forest classifier is used which is trained by twelve different features to find the boundaries between layers. Whats more, the relative gray feature and the neighbor features are used to solve the problem of large errors under the condition of uneven illumination. In the last, the segmentation results of the proposed algorithm, a traditional algorithm and Iowa segmentation software on ten sets of retinal images are compared with manual segmentation, and the average absolute boundary errors are 9.202.57m, 11.332.99m, 10.273.01m, respectively. The experiments show that the proposed algorithm can segment the Retinal Never Fiber Layer (RNFL) better.
- Spectral Domain Optical Coherence Tomography (SD-OCT) /
- Glaucoma /
- Retinal image segmentation /
- Retinal Never Fiber Layer (RNFL) /
- Random forest

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参考文献(14)

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