用于眼底图像中血管参数定量测量的软件

IF 5.4 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Xiaolong Zhu , Wenjian Li , Weihang Zhang , Jing Liu , Yue Qi , Qiuju Deng , Huiqi Li
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引用次数: 0

摘要

视网膜血管是一种独特的结构,可以对微循环系统进行无创观察。其病理特征和异常结构改变与心血管和全身性疾病有关。尤其是视网膜血管的口径特征、组织学特征和几何结构的异常是这些疾病的征兆。然而,血管的复杂分布和不易察觉的特性阻碍了血管参数的测量。为此,我们设计了一款新软件(视网膜血管参数定量测量软件,RVPQMS)来定量测量视网膜血管的特征。RVPQMS 具有血管分割、地标定位、血管跟踪、血管识别和参数测量等功能。它能全面测量标准区域和整个区域的血管参数。为确保软件的准确性,该软件集成的算法在私有和公共数据集上进行了验证,实验结果表明,该软件在血管分割、跟踪和识别方面具有出色的性能。RVPQMS 软件能全面、定量地测量视网膜血管参数,有助于研究心血管和系统疾病的血管特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A software for quantitative measurement of vessel parameters in fundus images
Retinal vessel is a unique structure that allows non-invasive observation of the microcirculatory system. Its pathological features and abnormal structural alterations are associated with cardiovascular and systemic diseases. Especially the abnormalities in caliber features, histology features, and geometric structure of retinal vessels are indicative of these diseases. However, the complex distribution and imperceptible characteristics of vasculature have hindered the measurement of vessel parameters. To this end, we design a new software (Retinal Vessel Parameters Quantitative Measurement Software, RVPQMS) to quantitatively measure the features of retinal vessels. The RVPQMS is designed with the functions of vessel segmentation, landmark localization, vessel tracking, vessel identification and parameter measurement. It enables comprehensive measurement of vessel parameters in both standard zone and whole area. To ensure the accuracy of the software, the algorithms integrated in this software are validated on both private and public datasets, and experimental results demonstrate that it has excellent performance in vessel segmentation, tracking and identification. The RVPQMS software provides thorough and quantitative measurement of retinal vessel parameters, facilitating the study of vessel features for cardiovascular and systemic diseases.
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来源期刊
CiteScore
10.70
自引率
3.50%
发文量
71
审稿时长
26 days
期刊介绍: The purpose of the journal Computerized Medical Imaging and Graphics is to act as a source for the exchange of research results concerning algorithmic advances, development, and application of digital imaging in disease detection, diagnosis, intervention, prevention, precision medicine, and population health. Included in the journal will be articles on novel computerized imaging or visualization techniques, including artificial intelligence and machine learning, augmented reality for surgical planning and guidance, big biomedical data visualization, computer-aided diagnosis, computerized-robotic surgery, image-guided therapy, imaging scanning and reconstruction, mobile and tele-imaging, radiomics, and imaging integration and modeling with other information relevant to digital health. The types of biomedical imaging include: magnetic resonance, computed tomography, ultrasound, nuclear medicine, X-ray, microwave, optical and multi-photon microscopy, video and sensory imaging, and the convergence of biomedical images with other non-imaging datasets.
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