Abstract:
Introduction: The management of medical images has been gaining followers based on the
advantages it offers for the diagnosis of diseases, which, like COVID-19, present with
clinical manifestations that can be captured in the form of images.
Objective: Take advantage of the quasi-periodicity of the principal components (PCs) in
the decomposition into PCs of medical images, which represent dermatological
manifestations in paucisymptomatic patients of COVID-19.
Methodology: Here, a set of photos was taken of one of the most frequent patterns in
COVID-19, the maculopapular pattern, characterized by an erythmatopapular rash, and
compression of one of the medical images was performed. Said compression was carried
out in different ways: (1) using two PCs, (2) using both a periodic PC and a non-periodic
PC, (3) using two periodic PCs, (4) using a single PC, and (5) using a single periodic PC.Result: The results of this research proved that it is possible to work with acceptable
reconstructions of compressed images in the field of dermatology, without losing the quality
and characteristics that allow to reach a correct diagnosis. In addition, this achievement
permits to correctly classify many diseases without fear of being wrong.
Conclusion: With the method presented, the use of a robust medical image compression
technique that could be very useful in the field of health is proposed. The images allow the
diagnosis of diseases such as COVID-19 in paucisymptomatic patients, understanding them
allows minimizing their weight without losing quality, which facilitates their use and
storage.
