Effect of Ultrasound Images Based on Filtering Algorithm on the Diagnosis Efficiency of Cervical Lymph Node Tuberculosis

Author:

Hu Chenchan,Zhou Fan,Zhu Liya,Su Feifei,Zhou Chen

Abstract

Objective: This paper uses filtering algorithms to explore and analyze the characteristics of cervical tuberculous lymph nodes and metastatic lymph nodes in ultrasound sonograms. Methods: 160 lymph nodes of 105 patients who obtained pathological results were retrospectively analyzed in this paper, including 76 tuberculous lymph nodes and 84 metastatic lymph nodes. The following ultrasound findings of lymph nodes in the two groups were compared: L/S, border, lymphatic door, internal echo, calcification, necrosis and liquefaction, and their characteristics were analyzed. Results: Both calcifications and liquid echoless areas were present in both groups. The internal calcifications of metastatic lymph nodes were mostly micro-calcifications, which were clustered, and the tuberculous lymph nodes were mostly scattered coarse calcifications. The difference was statistically significant (P < 0.01). The liquefaction area in metastatic lymph nodes was mostly eccentric and the area ratio was less than 50%. The liquefaction area in tuberculous lymph nodes was mostly in the center and the area ratio was more than 50%. The difference was statistically significant (P < 0 01). Conclusion: Ultrasound imaging features such as the size and distribution of calcification, and the location and area ratio of liquefaction zone are helpful to distinguish tuberculous lymph nodes from metastatic lymph nodes.

Publisher

American Scientific Publishers

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3