Early Detection of Skin Disorders and Diseases Using Radiometry

Diagnostics (Basel). 2022 Aug 31;12(9):2117. doi: 10.3390/diagnostics12092117.

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.

Keywords: basal cell carcinoma (BCC); diseased skin; millimeter-wave; non-contact diagnoses; radiometry; skin reflectance; squamous cell carcinoma (SCC).

Grants and funding

This research received no external funding. The paper is part of the research and collaboration activities for the UNESCO Chair in Data Science for Sustainable Development at the Arab American University—Palestine, Chairholder Dr. Majdi Owda.