摘要
图像分割在图像处理中处于至关重要的地位,分割的效果将直接影响到后续对图像的处理。视网膜血管是人体的重要组成部分,其血管网络形态结构的影响,是心脑血管疾病对血管微循环检查的重要部位。因此,对血管的研究具有实际意义,尤其在临床上的应用更是普及。本文通过对血管分割方法的大量研究,针对当前比较流行的方法进行了阐述。最后对最流行的深度学习算法在医学上的应用进行探索。通过对多种血管分割方法的研究,从而提高眼底病临床诊断的效率与精度,给DR的进一步治疗提供理论依据,进而协助临床眼底病变的早期发现和诊断。
Image segmentation is in a crucial position in image processing, and the effect of segmentation will directly affect the subsequent processing of images. Retinal blood vessels are an important part of the human body, and the influence of the vascular network morphology and structure is an important part of cardiovascular and cerebrovascular diseases for the examination of vascular microcirculation. Therefore, the reasearch of blood vessels has practical significance, especially in clinical applications. In this paper, through a lot of research on the method of blood vessel segmentation, the current popular methods are expounded. Finally, the application of the most popular deep learning algorithms in medicine is explored.Through the research of a large number of blood vessel segmentation methods, the efficiency and accuracy of clinical diagnosis of fundus diseases can be improved, and the theoretical basis for further treatment of DR can be provided to assist in the early detection and diagnosis of clinical fundus lesions.
引文
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