Kipli Kuryati, Hoque Mohammed Enamul, Lim Lik Thai, Mahmood Muhammad Hamdi, Sahari Siti Kudnie, Sapawi Rohana, Rajaee Nordiana, Joseph Annie
Department of Electrical and Electronics Engineering, University Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Kuching, Malaysia.
Department of Ophthalmology, Faculty of Medicine and Health Sciences (FMHS), University Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, Malaysia.
Comput Math Methods Med. 2018 Jul 2;2018:4019538. doi: 10.1155/2018/4019538. eCollection 2018.
Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric features measurements such as vessel tortuosity, branching angles, branching coefficient, vessel diameter, and fractal dimension. These extracted markers or characterized fundus digital image features provide insights and relates quantitative retinal vascular topography abnormalities to various pathologies such as diabetic retinopathy, macular degeneration, hypertensive retinopathy, transient ischemic attack, neovascular glaucoma, and cardiovascular diseases. Apart from that, this noninvasive research tool is automated, allowing it to be used in large-scale screening programs, and all are described in this present review paper. This paper will also review recent research on the image processing-based extraction techniques of the quantitative retinal microvascular feature. It mainly focuses on features associated with the early symptom of transient ischemic attack or sharp stroke.
数字图像处理是生物医学工程中应用最广泛的计算机视觉技术之一。在现代眼科实践中，通过数字眼底图像处理分析进行生物标志物分析对视觉科学有很大贡献。这进一步推动了医学成像的发展，使这项强大的技术在生物医学工程平台上有广泛的应用范围。各种诊断技术用于分析视网膜微血管图像，以实现诸如血管迂曲度、分支角度、分支系数、血管直径和分形维数等几何特征的测量。这些提取的标志物或特征化的眼底数字图像特征提供了见解，并将视网膜血管定量地形异常与各种疾病联系起来，如糖尿病视网膜病变、黄斑变性、高血压视网膜病变、短暂性脑缺血发作、新生血管性青光眼和心血管疾病。除此之外，这种非侵入性研究工具是自动化的，可用于大规模筛查项目，本文将对所有这些内容进行描述。本文还将综述基于图像处理的定量视网膜微血管特征提取技术的最新研究。它主要关注与短暂性脑缺血发作或急性中风早期症状相关的特征。
