On October 17, 2025, the seminar with Pierangela Brunoill take place.

A map to the location can be found on TU Maps.

Abstract

Deep learning emerged as a transformative technology in healthcare, particularly in medical imaging. Deep learning methods enable effective detection, segmentation, and classification of pathologies, improving the accuracy and robustness of image analysis. These advances are shaping modern medical practice and paving the way toward personalized medicine. In this talk I will provide an overview of common deep learning approaches for medical image analysis, highlighting recent advancements, innovative techniques, and real-world applications

About the Speaker

Pierangela Bruno, PhD, got a master’s degree within a Dual Degree Program: Computer Science (University of Calabria, 2017) and Software Engineering (University of Applied Science of Upper Austria, 2017). She received her PhD in Mathematics and Computer Science from the University of Calabria (2021). She has been a visiting PhD student at the Department of Computer-Assisted Medical Interventions (German Cancer Research Center), Heidelberg, Germany, and a post-doc at the Department of Mathematics and Computer Science (University of Calabria, 2021). Since 2022, she serves as a non-tenured Assistant Professor (RtdA) in the same Department. Her main research interests involve Deep Learning-based approaches for analyzing biomedical images and data, to provide an automated assessment of pathological conditions, identifying latent relationships across different domains, and detecting and segmenting specific elements of medical interest.