基于群体智能和变换函数的血管视网膜图像分析

R. Malik, Megha Shrivastava, Vikaram Singh Takur
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引用次数: 0

摘要

图像处理在医学疾病诊断中起着至关重要的作用,可以预测糖尿病、心脏血管问题和心脏病发作等严重问题。对于严重程度的预测,这样的问题采用了自动血管分割。对于自动血液分割,使用了各种算法和技术。但在血管分割中,灵敏度和准确性存在一定的问题。本文提出了基于Gabor变换函数、FCM算法和蚁群优化的血管分割方法。我们设计的算法在视网膜图像的精度和灵敏度方面都是非常有效的。血管分割过程的实用性要求提高分割面积和提高分割效率的价值——图像分割方法的发展采用阈值法和一些目标函数优化方法。精确的函数优化方法增加了分割面积,提高了灵敏度值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Retinal Image for Blood Vessel Using Swarm Intelligence and Transform Function
Image processing plays a vital role in diagnosing medical diseases for the prediction of critical problems such as diabetes, the vascular problem of heart, and heart attack. For the prediction of severe, such a problem used automatic blood vessel segmentation. For automatic blood segmentation, various algorithms and techniques are used. But some sensitivity and accuracy are a significant issue in blood vessel segmentation. In this paper proposed blood vessel segmentation using Gabor transform function, FCM algorithm, and ant colony optimization. Our designed algorithm is very efficient in terms of the accuracy and sensitivity of the retinal image. The utility of the blood vessel segmentation process demands the improvement of the segmentation area and increase the value of efficiency-the development of the image-segmentation method used threshold method with some objective function optimization method. The accurate function optimization method increases the segmentation area and increases the value of sensitivity.
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