Nautical Science Deptartment, Faculty of Maritime, King Abdul Aziz University, Jeddah, Saudia Arabia.
Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology Larkana Campus, Sukkur, Pakistan.
PLoS One. 2023 Jul 19;18(7):e0288792. doi: 10.1371/journal.pone.0288792. eCollection 2023.
Eye diseases such as diabetic retinopathy are progressive with various changes in the retinal vessels, and it is difficult to analyze the disease for future treatment. There are many computerized algorithms implemented for retinal vessel segmentation, but the tiny vessels drop off, impacting the performance of the overall algorithms. This research work contains the new image processing techniques such as enhancement filters, coherence filters and binary thresholding techniques to handle the different color retinal fundus image problems to achieve a vessel image that is well-segmented, and the proposed algorithm has improved performance over existing work. Our developed technique incorporates morphological techniques to address the center light reflex issue. Additionally, to effectively resolve the problem of insufficient and varying contrast, our developed technique employs homomorphic methods and Wiener filtering. Coherent filters are used to address the coherence issue of the retina vessels, and then a double thresholding technique is applied with image reconstruction to achieve a correctly segmented vessel image. The results of our developed technique were evaluated using the STARE and DRIVE datasets and it achieves an accuracy of about 0.96 and a sensitivity of 0.81. The performance obtained from our proposed method proved the capability of the method which can be used by ophthalmology experts to diagnose ocular abnormalities and recommended for further treatment.
眼部疾病，如糖尿病性视网膜病变，是渐进性的，视网膜血管会发生各种变化，因此难以分析疾病以进行未来治疗。已经有许多用于视网膜血管分割的计算机化算法，但细小血管会脱落，影响整体算法的性能。这项研究工作包含了新的图像处理技术，如增强滤波器、相干滤波器和二值化阈值技术，以处理不同颜色眼底图像的问题，从而实现分割良好的血管图像，并且所提出的算法在性能上优于现有工作。我们开发的技术结合了形态学技术来解决中心光反射问题。此外，为了有效地解决对比度不足和变化的问题，我们开发的技术采用了同态方法和维纳滤波。相干滤波器用于解决视网膜血管的相干性问题，然后应用双阈值技术和图像重建来实现正确分割的血管图像。我们开发的技术的结果使用 STARE 和 DRIVE 数据集进行了评估，其准确率约为 0.96，灵敏度为 0.81。从我们提出的方法中获得的性能证明了该方法的能力，该方法可以由眼科专家用于诊断眼部异常并推荐进一步治疗。
