Description:
The goal of this project is to perform a comparative study of state-of-the-art deep learning models for segmentation of mobile-acquired dermatological images. Particularly, the following application scenarios in dermatology involving handheld image acquisition will be explored:
1) Skin lesions (melanocytic and nonmelanocytic lesions);
2) Skin wounds (pressure ulcers, traumatic/surgical wounds and bruises).
Outcome:
Expand AICOS’ background knowledge in segmentation strategies based on deep learning, with expected direct impact in current and future Derma portfolio projects such as MpDS, MDevNet and DermAI.
Author: Catarina Andrade
Type: MSc thesis
Partner: FEUP – Faculdade de Engenharia da Universidade do Porto
Year: 2020