童何俊, 付冬梅. 基于参考模型的视网膜特征量化[J]. 工程科学学报, 2019, 41(9): 1222-1227. DOI: 10.13374/j.issn2095-9389.2019.09.015
引用本文: 童何俊, 付冬梅. 基于参考模型的视网膜特征量化[J]. 工程科学学报, 2019, 41(9): 1222-1227. DOI: 10.13374/j.issn2095-9389.2019.09.015
TONG He-jun, FU Dong-mei. Retinal feature quantization method based on a reference model[J]. Chinese Journal of Engineering, 2019, 41(9): 1222-1227. DOI: 10.13374/j.issn2095-9389.2019.09.015
Citation: TONG He-jun, FU Dong-mei. Retinal feature quantization method based on a reference model[J]. Chinese Journal of Engineering, 2019, 41(9): 1222-1227. DOI: 10.13374/j.issn2095-9389.2019.09.015

基于参考模型的视网膜特征量化

Retinal feature quantization method based on a reference model

  • 摘要: 提出一种基于参考模型的视网膜特征量化方法,结合医生诊断过程中关注的视网膜形态变化特征,提出一系列适用于计算机判断分析视网膜状态的可量化特征.在完成正常光学相干断层成像(OCT)中视网膜内界膜(ILM)、光感受器内外节交界处(ISOS)、布鲁赫膜(BM)分割提取的基础上,利用统计方法构建正常视网膜参考模型.结合参考模型和医生所关注的视网膜厚度、边界平滑度以及边界连续性,实现视网膜不同区域厚度特征、厚度比值特征、梯度特征、曲率、标准差、相关系数特征的计算.基于正常OCT图像所构建的参考模型,获取了正常视网膜的厚度及形态特征量化数值.通过分析比较异常OCT图像与参考模型特征数值之间的差异,可以对应表征出异常图像中病变导致的异常形态所在位置及严重程度.实验结果表明,通过参考模型获得的正常视网膜特征信息可以为医生提供数值参考,同时对异常OCT图像量化得到的特征数值可以表现出图像中的异常形态,为后续的异常判断提供基础.

     

    Abstract: Optical coherence tomography (OCT) plays an important role in the diagnosis of ocular fundus diseases. Retinal OCT images contain a large amount of useful information for the diagnosis of ocular fundus diseases and are often used to detect small lesions of the fundus. At present, many medical researchers have used OCT to determine the statistical characteristics of the retina to analyze various fundus diseases. When interpreting the OCT images, ophthalmologists will focus on the location of the lesions in the images and the characteristic morphology conducive to abnormal judgment and compare the histological structure of specific objects in the images with the known normal morphology. In the comparison process, the ophthalmologist will conduct a variety of quantitative analyses of OCT retinal images and determine the severity of the abnormalities and the location of the lesions. Finally, on the basis of the differences between the morphologies and types of diseases, the diagnostic decision is obtained. However, at present, OCT instruments generally only provide the thickness, area, and other commonly used characteristic data, and these data are often inadequate to determine the disease. Computer graphics processing technology has been applied to the auxiliary analysis of OCT images. However, this kind of research often confines the object of study to several specific fundus diseases and makes targeted selection of quantitative features. In the actual diagnosis process, it is difficult to confine the retinal images to some known abnormal cases because of the complexity of the situation. In this study, a retinal feature quantization method based on a reference model was proposed, and a series of quantifiable features suitable for computer judgment and analysis of retinal state were proposed. On the basis of the segmentation and extraction of the internal limiting membrane (ILM), junctions of the inner and outer segments of photoreceptors (ISOS) and Bruch's membrane (BM) in normal OCT images, a reference model of normal retina was constructed by the statistical method. Combining the reference model with the retinal thickness, smoothness, and continuity, the thickness characteristics, thickness ratio characteristics, gradient characteristics, curvature, standard deviation, and correlation coefficient characteristics of different regions of the retina were calculated. On the basis of the reference model of normal OCT images, the quantitative values of retinal thickness and morphological characteristics were obtained. By analyzing and comparing the characteristic value differences between abnormal OCT images and reference model, the location and severity of abnormal morphology caused by lesions could be characterized in the abnormal OCT images. The experimental results show that the normal retinal feature information obtained by the reference model can provide a numerical reference for ophthalmologists. At the same time, the characteristic values obtained by quantizing the abnormal OCT images can show the abnormal morphology, which provides a basis for subsequent abnormal judgment.

     

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