AI for Health @ Microsoft

VRAI Lab is happy to share that our Information Engineering Department (DII) at Università Politecnica delle Marche was granted by Microsoft AI for Health COVID-19 programme with our project aiCOVID19!
We try to join our forces with international researchers worldwide to combat the new coronavirus epidemic and to understand its aftermath. 

Info on the Microsoft AI for Health project:

Joint efforts during the course "Computer Vision and Deep Learning"

We are happy to announce that our work "A regression framework to head-circumference delineation from US fetal images" has been published in "Computer Methods and Programs in Biomedicine". You can find the work here:

This work was born in the framework of the "Computer Vision and Deep Learning" course of UNIVPM, held by Prof. Emanuele Frontoni. During the practical section of the course, two master students (Morriss Capparuccini and Sara Giamberini) started to work on fetal head-circumference delineation with the support and supervision of Maria Chiara Fiorentino (PhD student) and Sara Moccia (Postdoc). All the efforts have now been paid off!

Well done!

AI Technologies and Applications in Media Environments @ ABU Technology Webinar

Prof. Emanuele Frontoni gave a talk for the Asia Pacific Broadcasting Union on "AI Technologies and Applications in Media Environments", in cooperation with Tecla System & Università Politecnica delle Marche.

ABU (Asia-Pacific Broadcasting Union), established in 1964, is the biggest broadcasting union in the world.

Following the link of the talk:

Clinical Needs Translational Award (CTA) @ CinC2020

Dr. Sara Moccia has been awarded with the "Clinical Needs Translational Award (CTA)" in the framework of Computing in Cardiology 2020 (CinC2020, for the work:

"A Novel Approach based on Spatio-temporal Features and Random Forest for Scar Detection using Cine Cardiac Magnetic Resonance Images"

The work has been carried out in collaboration with Politecnico di Milano, Azienda Ospedaliera-Universitaria di Parma and Centro Cardiologico Monzino IRCCS.

Congratulation, Sara!



ULTIMATE WATER EU Kick-off Meeting

VRAI group successfully partecipated at the @ULTIMATEWaterEU kick-off meeting! 2 days with interesting talks about the project: getting to know partners, #demosites & tasks in the different work packages. Looking forward to the work on #CircularEconomy & #WaterSmartIndustrialSymbiosis!

Integrating Sensor Fusion and Perception for Human-robot Interaction @ IEEE RO-MAN 2020

During IEEE RO-MAN 2020 (, which will be held online from Aug, 31st to Sep, 4th 2020, the VRAI PostDoc Sara Moccia will co-chair and be part of the organization commitee of the workshop Integrating Sensor Fusion and Perception for Human-robot Interaction.

The workshop organization commitee calls for abstracts to discuss existing challenges, new ideas and resources and disseminate the latest results. For more details visit the workshop website

Workshop attendance and participation will be free of charge. 

VRAI MSc-Thesis Dissertation

Our MSc students, Mariachiara Di Cosmo and Francesca Pia VIllani, succesfully presented their thesis work in the framework of the Master's degree programme in Biomedical Engineering at UNIVPM: 

1) (Di Cosmo) Deep Learning Based 2D-3D Registration System For Augmented Visualization In Image Guided Endovascular Surgery - VIDEO:

2) (Villani) Development of an Augmented Reality system based on marker tracking for robotic-assisted minimally invasive spine surgery - VIDEO:

The thesis work was developed in collaboration with Vicomtech (Spain), where the two students spent 6 months.

Congratulation to the new Biomedical Engineers of UNIVPM! 



VRAI @ PHD COURSE "3D tissue segmentation, modelling and deformation: From pre-operative to intra-operative image analysis" (POLIMI/UNIVR)

The PostDoc Sara Moccia gave a cycle of lectures during the PhD course "3D tissue segmentation, modelling and deformation: From pre-operative to intra-operative image analysis" at Politecnico di Milano (POLIMI) and Università degli Studi di Verona (UNIVR). The lectures addressed the topic of deep learning applied to the analysis of  pre- and intra-operative images, with a focus on tissue segmentation.   

More information are available at this link: