论文标题
部分可观测时空混沌系统的无模型预测
A Survey on Automated Diagnosis of Alzheimer's Disease Using Optical Coherence Tomography and Angiography
论文作者
论文摘要
视网膜光学相干断层扫描（OCT）和光学相干断层扫描（OCTA）是（早期）诊断阿尔茨海默氏病（AD）的有前途的工具。这些非侵入性成像技术比替代神经影像工具更具成本效益，更容易获得。但是，即使对训练有素的从业人员来说，解释和分类的OCT设备进行的多层扫描也很耗时，而且具有挑战性。 关于机器学习和深度学习方法的调查，以对各种疾病（例如青光眼）进行OCT扫描的自动分析。但是，目前的文献缺乏对使用OCT或OCTA诊断阿尔茨海默氏病或认知障碍的广泛调查。这促使我们进行了针对需要介绍该问题的机器/深度学习科学家或从业者的全面调查。 The paper contains 1) an introduction to the medical background of Alzheimer's Disease and Cognitive Impairment and their diagnosis using OCT and OCTA imaging modalities, 2) a review of various technical proposals for the problem and the sub-problems from an automated analysis perspective, 3) a systematic review of the recent deep learning studies and available OCT/OCTA datasets directly aimed at the diagnosis of Alzheimer's Disease and Cognitive Impairment.对于后者，我们使用出版或灭亡软件来搜索来自Scopus，PubMed和Web的各种来源的相关研究。我们遵循Prisma方法筛选了3073参考的初始库，并确定了直接针对AD诊断的十项相关研究（n = 10，3073）。我们认为缺乏开放的OCT/OCTA数据集（关于阿尔茨海默氏病）是阻碍该领域进展的主要问题。
Retinal optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) are promising tools for the (early) diagnosis of Alzheimer's disease (AD). These non-invasive imaging techniques are cost-effective and more accessible than alternative neuroimaging tools. However, interpreting and classifying multi-slice scans produced by OCT devices is time-consuming and challenging even for trained practitioners. There are surveys on machine learning and deep learning approaches concerning the automated analysis of OCT scans for various diseases such as glaucoma. However, the current literature lacks an extensive survey on the diagnosis of Alzheimer's disease or cognitive impairment using OCT or OCTA. This has motivated us to do a comprehensive survey aimed at machine/deep learning scientists or practitioners who require an introduction to the problem. The paper contains 1) an introduction to the medical background of Alzheimer's Disease and Cognitive Impairment and their diagnosis using OCT and OCTA imaging modalities, 2) a review of various technical proposals for the problem and the sub-problems from an automated analysis perspective, 3) a systematic review of the recent deep learning studies and available OCT/OCTA datasets directly aimed at the diagnosis of Alzheimer's Disease and Cognitive Impairment. For the latter, we used Publish or Perish Software to search for the relevant studies from various sources such as Scopus, PubMed, and Web of Science. We followed the PRISMA approach to screen an initial pool of 3073 references and determined ten relevant studies (N=10, out of 3073) that directly targeted AD diagnosis. We identified the lack of open OCT/OCTA datasets (about Alzheimer's disease) as the main issue that is impeding the progress in the field.
