论文标题
使用一袋特征在OCT图像中自动检测微型神经瘤
Automatic Detection of Microaneurysms in OCT Images Using Bag of Features
论文作者
论文摘要
由糖尿病引起的糖尿病性视网膜病（DR）是由于视网膜血管的变化而导致的，并导致视觉障碍。微型干扰素（MAS）是DR的早期临床迹象，其及时诊断可以帮助在其发育的早期阶段检测DR。已经观察到，与患有DR的眼睛的视网膜外层相比，MAS在内部视网膜层中更为常见。光学相干断层扫描（OCT）是一种无创成像技术，可提供视网膜的横截面视图，近年来已用于诊断许多眼部疾病。结果，本文试图使用OCT图像识别来自视网膜正常区域的MA的区域。这项工作是使用20名DR患者的FA和OCT图像收集的数据集完成的。在这方面，首先注册了荧光素血管造影（FA）和OCT图像。然后将MA和正常区域分开，并使用特征袋（BOF）方法提取这些区域的特征，并具有加速鲁棒特征（Surf）描述符。最后，使用多层perceptron网络进行分类过程。对于准确性，灵敏度，特异性和精度的每个标准，所获得的结果分别为96.33％，97.33％，95.4％和95.28％。利用OCT图像来检测MASAUTOMPION，这是一个新想法，作为该领域的初步研究获得的结果是有希望的。
Diabetic Retinopathy (DR) caused by diabetes occurs as a result of changes in the retinal vessels and causes visual impairment. Microaneurysms (MAs) are the early clinical signs of DR, whose timely diagnosis can help detecting DR in the early stages of its development. It has been observed that MAs are more common in the inner retinal layers compared to the outer retinal layers in eyes suffering from DR. Optical Coherence Tomography (OCT) is a noninvasive imaging technique that provides a cross-sectional view of the retina and it has been used in recent years to diagnose many eye diseases. As a result, in this paper has attempted to identify areas with MA from normal areas of the retina using OCT images. This work is done using the dataset collected from FA and OCT images of 20 patients with DR. In this regard, firstly Fluorescein Angiography (FA) and OCT images were registered. Then the MA and normal areas were separated and the features of each of these areas were extracted using the Bag of Features (BOF) approach with Speeded-Up Robust Feature (SURF) descriptor. Finally, the classification process was performed using a multilayer perceptron network. For each of the criteria of accuracy, sensitivity, specificity, and precision, the obtained results were 96.33%, 97.33%, 95.4%, and 95.28%, respectively. Utilizing OCT images to detect MAsautomatically is a new idea and the results obtained as preliminary research in this field are promising .
