摘要
血管形态的变化与疾病密切相关,血管直径是血管形态的主要参数之一,测量血管直径有助于疾病的筛查与预防。提出一种基于聚类算法的血管直径测量方法,对微血管进行测量。大多数显微血管图像(如光学显微成像或光声显微成像)中存在噪声,通过非线性变换函数对显微图像进行增强;使用训练后的U-Net网络模型进行图像分割;利用结合聚类算法以及射线算法的测量方法对分割得到的血管进行测量,得到血管直径。实验表明,算法与传统测量结果一致(P>0.05),与传统算法相比,本算法的测量精度得到提升,将测量误差由4.21%降低至2.27%,满足血管测量的准确度需求。
Changes of blood vessel morphology are closely related to disease.Diameter is the main parameter of blood vessel morphology and measurement of blood vessel diameter is beneficial to the screening and prevention of diseases.A method of measuring blood vessel diameter based on clustering algorithm was proposed to measure microvessels.Noise is present in most microvascular images(such as optical or photoacoustic microimaging)and the microimages can be enhanced by nonlinear transformation functions.Trained U-Net network model was used to achieve extraction of retinal vessels.The blood vessel diameter was measured by combining clustering algorithm and ray algorithm.Experiments show that this proposed algorithm was consistent with the traditional measurement results(P>0.05).Compared with the traditional algorithm,the measurement accuracy of this algorithm was improved,and the measurement error was reduced from 4.21%to 2.27%,which meets the accuracy requirement of vascular measurement.
作者
王成
李砚瑞
刘宾
项华中
徐康
郑刚
陈明惠
张大伟
WANG Cheng;LI Yanrui;LIU Bin;XIANG HuazhongXU Kang;ZHENG Gang;CHEN Minghui;ZHANG Dawei(Institute of Biomedical Optics and Optometry,Key Lab of Medical Optical Technology and Instruments,Ministry of Education,University of Shanghai for Science and Technology,Shanghai 200093,China;Engineering Research Center of Optical Instrument and System,Ministry of Education,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《光学技术》
CAS
CSCD
北大核心
2021年第1期37-44,共8页
Optical Technique
基金
国家自然科学基金(61775140)。
关键词
图像处理
血管宽度
图像分割
U-Net
聚类算法
image processing
vessel width
image segmentation
U-Net
clustering algorithm
