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Publication
Deep learning in the identification of psoriatic skin lesions
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Advisor(s)
Abstract(s)
Psoriasis is a dermatological lesion that manifests in several
regions of the body. Its late diagnosis can generate the aggravation of
the disease itself, as well as of the comorbidities associated with it. The
proposed work presents a computational system for image classification
in smartphones, through deep convolutional neural networks, to assist
the process of diagnosis of psoriasis.
The dataset and the classification algorithms used revealed that the classification
of psoriasis lesions was most accurate with unsegmented and
unprocessed images, indicating that deep learning networks are able to do
a good feature selection. Smaller models have a lower accuracy, although
they are more adequate for environments with power and memory restrictions,
such as smartphones.
Description
Keywords
Image processing Deep learning Psoriasis classification Mobile application
Pedagogical Context
Citation
Lima, Gabriel Lenin Silva; Pires, Carolina; Beuren, Arlete Teresinha; Lopes, Rui Pedro (2024). Deep learning in the identification of psoriatic skin lesions. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP). Cham: Springer. 14469, p. 298-313. ISBN 978-3-031-49017-0