The purpose of this paper is to implement a computer-aided diagnosis (CAD) system for multiple sclerosis (MS) based on analysing the outer retina as assessed by multifocal electroretinograms (mfERGs). MfERG recordings taken with the RETI‐port/scan 21 (Roland Consult) device from 15 eyes of patients diagnosed with incipient relapsing-remitting MS and without prior optic neuritis, and from 6 eyes of control subjects, are selected. The mfERG recordings are grouped (whole macular visual field, five rings, and four quadrants). For each group, the correlation with a normative database of adaptively filtered signals, based on empirical model decomposition (EMD) and three features from the continuous wavelet transform (CWT) domain, are obtained. Of the initial 40 features, the 4 most relevant are selected in two stages: a) using a filter method and b) using a wrapper-feature selection method. The Support Vector Machine (SVM) is used as a classifier. With the optimal CAD configuration, a Matthews correlation coefficient value of 0.89 (accuracy = 0.95, specificity = 1.0 and sensitivity = 0.93) is obtained. This study identified an outer retina dysfunction in patients with recent MS by analysing the outer retina responses in the mfERG and employing an SVM as a classifier. In conclusion, a promising new electrophysiological-biomarker method based on feature fusion for MS diagnosis was identified.

本文的目的是基于多焦点视网膜电图 (mfERG) 评估的外视网膜分析，实现多发性硬化症 (MS) 的计算机辅助诊断 (CAD) 系统。选择使用 RETI-port/scan 21 (Roland Consult) 设备从诊断为早期复发缓解型多发性硬化症且既往无视神经炎的患者的 15 只眼睛以及对照受试者的 6 只眼睛获取的 MfERG 记录。mfERG 记录被分组（整个黄斑视野、五个环和四个象限）。对于每组，基于经验模型分解 (EMD) 和连续小波变换 (CWT) 域的三个特征，获得与自适应滤波信号规范数据库的相关性。在最初的 40 个特征中，分两个阶段选择 4 个最相关的特征：a) 使用过滤方法，b) 使用包装特征选择方法。支持向量机（SVM）用作分类器。采用最佳 CAD 配置时，马修斯相关系数值为 0.89（准确度 = 0.95，特异性 = 1.0，灵敏度 = 0.93）。这项研究通过分析 mfERG 中的外视网膜反应并采用 SVM 作为分类器，确定了近期患有多发性硬化症的患者的外视网膜功能障碍。总之，确定了一种基于特征融合的用于多发性硬化症诊断的有前景的新型电生理生物标志物方法。