PlenoISLA

This project focused on the development and implementation of new imaging techniques for non-invasive characterization of the skin surface, based on the light field (plenoptic) imaging technology. The main objective was to obtain a new set of 3D-based quantitative markers associated with physiological skin processes, enabling the characterization of morphological and functional skin structures and supporting their use in dermatological evolution and prognosis studies.

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Based on the extracted 3D skin characteristics, novel dermoholoscopic patterns were investigated, leading to the identification of feature clusters suitable for automatic analysis using machine learning methods, particularly deep learning approaches. In parallel with computational analysis, the project addressed new techniques for light field image acquisition and compression. Additionally, a database of plenoptic images of skin lesions was created (SKINL2) and made available to the scientific community, contributing to research in dermatological imaging and computer-aided diagnosis.