Special Session 20

SPECIAL SESSION #20

Selene Tomassini

University of Trento, Italy

• selene.tomassini@unitn.it

Niccolò Marini

University of Applied Sciences Western Switzerland (HES-SO Valais), Switzerland

• niccolo.marini@hevs.ch

Maria Chiara Fiorentino

Università Politecnica delle Marche, Italy

• m.c.fiorentino@staff.univpm.it

Nowadays, artificial intelligence, especially in the form of machine learning and deep learning, permeates our daily activities. Among artificial intelligence-based algorithms, convolutional neural networks and vision transformers are currently the core technologies for advanced medical image processing and analysis, often combined with recurrent modules or large language models in case of multimodal inputs.

Although artificial intelligence has achieved remarkable success in medical imaging tasks, its integration and usage as decision supporting tool in real clinical settings is still at the beginning. Thus, artificial intelligence-based cutting-edge technologies for advanced medical image processing and analysis are urgently needed, especially where data scarcity, data quality, and/or data interpretation and understanding are concrete issues.

This Special Session aims to collect original contributions on the design, development, and/or deployment of artificial intelligence-based cutting-edge technologies for advanced medical image processing and analysis.

Topics of interest for this Special Session include but are not limited to:

• artificial intelligence, machine learning and deep learning;
• on-the-edge artificial intelligence;
• generative models;
• federated learning paradigms;
• clinical decision-support systems;
• computer-aided detection, segmentation and diagnosis;
• ethics and explainability;
• medical imaging;
• medical image captioning;
• advanced medical image processing and analysis;
• medical image interpretation and understanding;
• medical image-guided interventions.

Selene Tomassini, obtained, in 2018, the MSc Degree in Biomedical Engineering at Università Politecnica delle Marche, Italy, graduating with honors. Her thesis focused on implementing a wavelet transform-based algorithm to automatically detect and identify fetal heart sounds.
In 2023, she got a PhD in Information Engineering curriculum Biomedical, Electronic and Telecommunication Engineering at the Department of Information Engineering of Università Politecnica delle Marche, Italy, defending a thesis entitled “On-cloud decision-support algorithms driven by deep learning in 3D radiological imaging diagnostics”.
Currently, she is an Assistant Professor at the Department of Information Engineering and Computer Science of University of Trento, Italy, mainly working on designing and developing artificial intelligence-based algorithms for processing and analysis of medical images, with a focus on clinical decision-support systems in radiodiagnostics.

Niccolò Marini, obtained, in 2018, the MSc Degree in Computer Science at Università Politecnica delle Marche, Italy, graduating with honors. His thesis focused on the adoption of deep learning to process and analyze lung computed tomography images.
In 2023, he got a PhD in Computer Science at University of Geneva, Switzerland, defending a thesis entitled “Deep learning methods to reduce the need for annotations for the extraction of knowledge from multimodal heterogeneous medical data”.
Currently, he is a PostDoc Assistant at University of Applied Sciences Western Switzerland (HES-SO Valais), Switzerland, mainly working on: developing automatic algorithms annotating data, aiming to alleviate the need for medical experts; developing algorithms leveraging heterogeneous data to improve the generalization of deep learning on unseen data; and developing algorithms combining multiple medical modalities to create a more robust representation of biomedical data.

Maria Chiara Fiorentino, obtained, in 2018, the MSc Degree in Biomedical Engineering at Università Politecnica delle Marche, Italy, graduating with honors. Her thesis focused on creating a detection system for Parkinson’s disease dyskinesia using consumer electronics, and received the Paolo Marziali Thesis Prize.
In 2023, she got a PhD in Information Engineering curriculum Computer, Management and Automation Engineering at the Department of Information Engineering of Università Politecnica delle Marche, Italy, defending a thesis entitled “DL4US: Unlocking the potential of deep learning for ultrasound image analysis”, which was awarded by the Gruppo Nazionale di Bioingegneria (National Association of Italian Bioengineering).
Currently, she is a PostDoc Researcher at the Department of Information Engineering of Università Politecnica delle Marche, working on designing and developing artificial intelligence-based algorithms for processing and analysis of medical images, including ultrasound, magnetic resonance and computed tomography ones.