Study on the methodology of striae gravidarum severity evaluation

Author:

Dai Hongyan,Liu Yangyang,Zhu Yan,Yu Yun,Meng Lin

Abstract

Abstract Background Striae gravidarum is a common occurrence in pregnancy and many women expect to prevent its development. At present, laser treatment has been used to improve the appearance of striae gravidarum, but the choice of laser type, treatment time, and frequency depend on the therapeutic effect. How to obtain an effective evaluation of striae gravidarum during and after treatment is very important. However, there is no unified evaluation parameter about striae gravidarum. In this paper, we studied the methodology evaluation of striae gravidarum severity. First, the laser therapeutic apparatus was selected as the experimental equipment and different striae gravidarum photos during treatment were obtained. Second, the subject evaluation parameters were chosen based on the literature research and the dermatologists’ guidance. Then, the striae gravidarum photos were divided into different groups by dermatologists based on these parameters. Finally, the objective detection parameters were designed based on the photos feature and subject evaluation parameters. Then, the objective detection parameters were used as the input of the support vector machine and the evaluation results were compared. Results Based on the subject evaluation parameters, the experimental data could be divided into mild, moderate and severe groups. The experiment results showed that the striae gravidarum severity of two randomly patients were improved before and after treatment, which verified the validity of the parameters. In addition, the chosen objective detection parameters were different among different groups. With all the objective parameters as the support vector machine input, we could achieve the best recognition rate (82.71%) in the striae gravidarum severity classification. The four parameters (color difference, average density, average width, distribution area) calculated from the photos as the input could achieve acceptable accuracy (81.69%). Conclusions The subject evaluation parameters and objective detection parameters proposed in this paper can be used to evaluate the striae gravidarum severity, which is of great significance for the construction of auxiliary diagnostic instrument for striae gravidarum treatment.

Funder

national natural science foundation of china

research fund of nanjing institute of technology

the 2018 project of jiangsu provincial university philosophy and social science research fund

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,General Medicine,Biomaterials,Radiological and Ultrasound Technology

Reference33 articles.

1. Wang F, Calderone K, Do T, Smith N, Helfrich Y, Johnson T, Kang S, Voorhees J, Fisher G. Severe disruption and disorganization of dermal collagen fibrils in early striae gravidarum. Br J Dermatol. 2018;178(3):e237.

2. Kan O, Gorkem U, Alkilic A, Cetin M. Efficacy of striae gravidarum extension and localization on predicting intraperitoneal adhesion risk. J Obstet Gynaecol Res. 2019;45(12):1–8.

3. Chen H, Zhang C, Wu H, Deng L, Li X. Clinical effect of gold microneedle radio-frequency in the treatment of striae gravidarum. Henan Med Res. 2019;1:1–2.

4. Brennan M, Clarke M, Devane D, Dowling M. A qualitative study of the factors influencing recruitment to a pilot trial on the prevention of striae gravidarum. BMC Pregnancy Childbirth. 2020;20(103):1–15.

5. Liu L, Huang J, Ying W, Li Y, Iratxe P. Risk factors of striae gravidarum in Chinese primiparous women. PLoS ONE. 2018;13(6):e0198720.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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