论文标题
紫红色 - 光学相干断层扫描的CNN体系结构
ClaRet -- A CNN Architecture for Optical Coherence Tomography
论文作者
论文摘要
光学相干断层扫描是一种用于扫描眼睛视网膜并检查眼泪的技术。在本文中，我们为OCT扫描分类开发了卷积神经网络体系结构。该模型经过训练，以检测OCT扫描中的视网膜撕裂并对撕裂的类型进行分类。我们设计了一种基于块的方法，可以使用转移学习伴随预训练的VGG-19，通过在块中编写自定义层以更好地提取特征。该方法比我们最初开始的基线取得了更好的结果。
Optical Coherence Tomography is a technique used to scan the Retina of the eye and check for tears. In this paper, we develop a Convolutional Neural Network Architecture for OCT scan classification. The model is trained to detect Retinal tears from an OCT scan and classify the type of tear. We designed a block-based approach to accompany a pre-trained VGG-19 using Transfer Learning by writing customised layers in blocks for better feature extraction. The approach achieved substantially better results than the baseline we initially started out with.
