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.

Methods:

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.

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