Detecting age-related macular degeneration (AMD) biomarker images using MFCC and texture features
Detecting age-related macular degeneration (AMD) biomarker images using MFCC and texture features
复制标题
使用 MFCC 和纹理特征检测年龄相关性黄斑变性 (AMD) 生物标志物图像
DOI：
10.1117/12.2551163
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Raicu, Daniela
中科院分区：
文献类型：
--
作者：
Wang, Yiyang;Ma, Xufan;Weddell, Rob;Okemgbo, Abum;Rein, David;Fawzi, Amani A.;Furst, Jacob;Raicu, Daniela
视网膜相关性黄斑变性（AMD）是老年人不可逆视力丧失的主要原因。在临床上，眼科医生目视检查光学相干断层扫描（OCT）体积，以基于众所周知的生物标志物诊断AMD的阶段。AMD的早期特征是玻璃疣，其表现为视网膜下的黄色沉积物。AMD主要分为两种类型：干性AMD（非新生血管性）和湿性AMD（新生血管性）。考虑到单个体积中的大量OCT图像，有效的计算机辅助检测系统可以通过自动检测相关图像中的生物标志物来减少眼科医生的工作量。由于RPE的形状在定义由湿性和干性AMD引起的病理变化中是至关重要的，因此我们提出了一种使用Mel频率倒谱系数（MFCC）来描述RPE形状的新方法。我们以前的工作表明，Haralick纹理特征有能力区分玻璃疣从健康组织的彩色摄影，因此，我们也研究了Haralick纹理特征提取的区域之间的内界膜（ILM）和Bruchs膜（BM）层在这项研究中。我们在测试集上实现了平均准确度，AMD图像的灵敏度和健康图像的特异性分别为89.68%，89.26%和90.12%，在新患者验证集上分别为69.22%，67.40%和75.56%。我们的二进制分类结果表明，MFCC是唯一适合于产生可推广的结果，以自动检测AMD生物标志物图像。
Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss in older individuals. Clinically, ophthalmologists visually inspect optical coherence tomography (OCT) volumes to diagnose the stage of AMD based on well-known biomarkers. An early characteristic of AMD is drusen, which appears as yellowish deposits under the retina. AMD is mainly categorized into two types: dry AMD (non-neovascular) and wet AMD (neovascular). Given the large number of OCT images in an individual volume, an efficacious computer-aided detection system can reduce the workload for ophthalmologists by automatically detecting biomarkers in the relevant images. Because the shape of the RPE is critical in defining the pathological changes caused by wet and dry AMD, we propose a novel approach to describe the RPE shape using Mel Frequency Cepstral Coefficients (MFCC). Our previous work indicates that Haralick texture features have the ability to distinguish drusen from healthy tissue on color photography, therefore, we also investigated Haralick texture features extracted from the region between Inner Limiting Membrane (ILM) and Bruchs Membrane (BM) layers in this study. We achieved a mean accuracy, sensitivity with respect to AMD image and specificity with respect to healthy image of 89.68%, 89.26% and 90.12% on testing sets and 69.22%, 67.40%, and 75.56% on new patient validation sets, respectively. Our binary classification results indicate that MFCC are uniquely suited for producing generalizable results to automatically detect AMD biomarker images.
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影响因子：
3.4
作者：
Yiyang Wang;Brian T. Soetikno;J. Furst;D. Raicu;A. Fawzi
通讯作者：
Yiyang Wang;Brian T. Soetikno;J. Furst;D. Raicu;A. Fawzi
影响因子：
13.7
作者：
Farsiu S;Chiu SJ;O'Connell RV;Folgar FA;Yuan E;Izatt JA;Toth CA;Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group
通讯作者：
Age-Related Eye Disease Study 2 Ancillary Spectral Domain Optical Coherence Tomography Study Group
影响因子：
8.1
作者：
Scarinci F;Jampol LM;Linsenmeier RA;Fawzi AA
通讯作者：
Fawzi AA
影响因子：
1.7
作者：
Gess, Adam J.;Fung, Anne E.;Rodriguez, Jorge G.
通讯作者：
Rodriguez, Jorge G.