NDLI: Study on the methodology of striae gravidarum severity evaluation

Content Provider	Springer Nature : BioMed Central
Author	Dai, Hongyan Liu, Yangyang Zhu, Yan Yu, Yun Meng, Lin
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.
Related Links	https://biomedical-engineering-online.biomedcentral.com/counter/pdf/10.1186/s12938-021-00945-w.pdf
Ending Page	12
Page Count	12
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s12938-021-00945-w
Journal	BioMedical Engineering OnLine
Issue Number	1
Volume Number	20
Language	English
Publisher	BioMed Central
Publisher Date	2021-10-25
Access Restriction	Open
Subject Keyword	Biomedical Engineering and Bioengineering Biomaterials Biotechnology Biomedical Engineering Striae gravidarum Laser treatment Evaluation parameters Support vector machine Biomedical Engineering/Biotechnology
Content Type	Text
Resource Type	Article
Subject	Biomaterials Radiological and Ultrasound Technology Biomedical Engineering Radiology, Nuclear Medicine and Imaging
Journal Impact Factor	2.9/2023
5-Year Journal Impact Factor	3.5/2023

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Correction to: Study on the methodology of striae gravidarum severity evaluation

Machine learning, medical diagnosis, and biomedical engineering research - commentary

Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

Atrial fibrillation detection by heart rate variability in Poincare plot

Correction to: Semivariogram and Semimadogram functions as descriptors for AMD diagnosis on SD-OCT topographic maps using Support Vector Machine

Automatic hand phantom map generation and detection using decomposition support vector machines

Valentinuzzi ME: Understanding the Human Machine, A Primer for Bioengineering

The development and evaluation of a computerized diagnosis scheme for pneumoconiosis on digital chest radiographs

Mathematical modeling of endovenous laser treatment (ELT)

Study on the methodology of striae gravidarum severity evaluation

Similar Documents

Correction to: Study on the methodology of striae gravidarum severity evaluation

Machine learning, medical diagnosis, and biomedical engineering research - commentary

Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

Atrial fibrillation detection by heart rate variability in Poincare plot

Correction to: Semivariogram and Semimadogram functions as descriptors for AMD diagnosis on SD-OCT topographic maps using Support Vector Machine

Automatic hand phantom map generation and detection using decomposition support vector machines

Valentinuzzi ME: Understanding the Human Machine, A Primer for Bioengineering

The development and evaluation of a computerized diagnosis scheme for pneumoconiosis on digital chest radiographs

Mathematical modeling of endovenous laser treatment (ELT)

Study on the methodology of striae gravidarum severity evaluation