Niccolò Marini successfully defended his PhD work on “Deep learning methods to reduce the need for annotations for the extraction of knowledge from multimodal heterogeneous medical data”.
His thesis focused on:
- how to alleviate the need for manual annotations to train deep learning algorithms
- how to leverage color variability to improve the CNN generalization on unseen data
- how to learn a more details WSI representation combining multiple magnification levels
- how to empower the raw-pixel level image representation introducing high-level concepts from textual reports
This work was co-supervised by Prof. Henning Müller and Prof. Manfredo Atzori, Institute of Informatics, University of Applied Sciences Western Switzerland (HESSO), Prof. Stephane Marchand-Maillet, Department of Computer Science, University of Geneva. Prof. Anne Martel, Department of Medical Biophysics, University of Toronto, completed the committee as international expert in the domain.
For more details, check his list of publications.
