Drusen diagnosis comparison between hyper-spectral and color retinal images.
Drusen diagnosis comparison between hyper-spectral and color retinal images.
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DOI：
10.1364/boe.10.000914
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发表时间：
2019-01
影响因子：
3.4
通讯作者：
Yiyang Wang;Brian T. Soetikno;J. Furst;D. Raicu;A. Fawzi
中科院分区：
文献类型：
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作者：
Yiyang Wang;Brian T. Soetikno;J. Furst;D. Raicu;A. Fawzi
年龄相关性黄斑变性(AMD)是一种退行性衰老疾病，可导致老年人不可逆转的视力丧失。视网膜高光谱成像临床应用的出现为捕捉重要的光谱特征提供了独特的机会，有可能提高视网膜疾病的分子诊断。在这项研究中，我们使用机器学习分类方法来探索与标准RGB图像相比，高光谱图像是否提供了更好的结果。我们的结果表明，与标准图像相比，该分类器在高光谱图像上的性能更好，对玻璃体分类的准确率和灵敏度都有所提高。通过检查分类任务中最重要的特征，我们的数据表明玻璃灰岩具有高度的异质性。我们的工作提供了进一步的证据，证明高光谱视网膜图像数据特别适合于计算机辅助诊断和检测技术。
Age-related macular degeneration (AMD) is a degenerative aging disorder, which can lead to irreversible vision loss in older individuals. The emergence of clinical applications of retinal hyper-spectral imaging provides a unique opportunity to capture important spectral signatures, with the potential to enhance the molecular diagnosis of retinal diseases. In this study, we use a machine learning classification approach to explore whether hyper-spectral images offer an improved outcome compared to standard RGB images. Our results show that the classifier performs better on hyper-spectral images with improved accuracy and sensitivity for drusen classification compared to standard imaging. By examining the most important features in the classification task, our data suggest that drusen are highly heterogeneous. Our work provides further evidence that hyper-spectral retinal image data are uniquely suited for computer-aided diagnosis and detection techniques.