Early Detection of Skin Disorders and Diseases Using Radiometry

Author:

Owda Amani YousefORCID,Owda MajdiORCID

Abstract

Skin diseases and disorders have a significant impact on people’s health and quality of life. Current medical practice suggests different methodologies for detecting and diagnosing skin diseases and conditions. Most of these require medical tests, laboratory analyses, images, and healthcare professionals to assess the results. This consumes time, money, and effort, and the waiting time is stressful for the patient. Therefore, it is an essential requirement to develop a new automatic method for the non-invasive diagnosis of skin diseases and disorders without the need for healthcare professionals or being in a medical clinic. This research proposes millimeter-wave (MMW) radiometry as a non-contact sensor for the non-invasive diagnosis of skin diseases and conditions. Reflectance measurements performed using 90 GHz radiometry were conducted on two samples of participants; sample 1 consisted of 60 participants (30 males and 30 females) with healthy skin, and sample 2 contained 60 participants (30 males and 30 females) suffering from skin diseases and conditions, which were: basal cell carcinoma (BCC), squamous cell carcinoma (SCC), burn wounds, and eczema. Radiometric measurements show substantial differences in reflectance in the range of 0.02–0.27 between healthy and unhealthy regions of the skin on the same person. These results indicate that radiometry, as a non-contact sensor, can identify and distinguish between healthy and diseased regions of the skin. This indicates the potential of using radiometry as a non-invasive technique for the early detection of skin diseases and disorders.

Publisher

MDPI AG

Subject

Clinical Biochemistry

Reference44 articles.

1. Skin 1: The structure and functions of the skin;Lawton;Clin. Pract. Syst. Life Ski.,2019

2. Human Skin https://en.wikipedia.org/wiki/Human_skin

3. Human Anatomy https://www.webmd.com/skin-problems-and-treatments/picture-of-the-skin

4. Better Health Channel;Department of Health,2021

5. Anatomy and Physiology 2e;Betts,2022

Cited by 1 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

1. Electrical Load Forecasting Based on Random Forest, XGBoost, and Linear Regression Algorithms;2023 International Conference on Information Technology (ICIT);2023-08-09

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