Digital pathology (DP) and artificial intelligence (AI) have revolutionized the field of pathology. Although growing interest in DP & AI has been observed recently, there is still a reluctance to adopt this technology in routine clinical practice. Further, there is a need to harmonize this technology globally and bridge the knowledge gaps to get acquainted with the nuances of DP & AI. To this aim, we are pleased to announce the first-ever edition of the EurAsia Academy on Digital Pathology, an online event that will take place on October 10, 2023.

Organized by the European Society of Digital and Integrative Pathology (ESDIP), the Japanese Society of Digital Pathology (JSDP), and the Indian DP Interest Group, this event will bring together top-level experts from across the globe.

Throughout the day, pathologists, technicians, computer scientists, and clinicians, from entry-level to experienced users, will be able to follow online lectures that will cover major topics related to DP and AI. In this symposium, the following key areas will be addressed in two separate sessions:
1. Establishing and Transitioning to Digital Pathology
2. AI algorithms: From basics to clinical adoption

Una lista di risorse utili per il minicorso su terminologie e classificazioni biomediche:

From 28th August to 1st September, 2023 the University of Udine will host the 1st MSCA BosomShield Summer School, devoted to Image Analysis for Biomedical Imaging and specifically for Radiology and Pathology.

bosomshield-logo

Final programme here: https://mitel.dimi.uniud.it/bosomshield/

Programme

Monday 28th August, 2023
8:45IntroductionV.Della Mea, C.Di Loreto, D.Puig
9:00Biopsies and WSI preparationC. Lopez, Laia Adalid
11:00Prognostic factors in breast cancerEnrico Pegolo
12:45Lunch break
14:00Introduction to AI in Digital Pathology: BackgroundIzidor Mlakar
16:00Introduction to WSI Image AnalysisAnna Korzynska
Tuesday 29th August, 2023
9:00MRI for breast cancer 1Rodrigo Moreno
11:00Medical imaging techniques for breast cancer 1A.Lalande
12:45Lunch break
14:00Medical imaging techniques for breast cancer 2A.Lalande
16:00Teamwork: practical activities
Wednesday 30th August, 2023
9:00MRI for breast cancer 2Rodrigo Moreno
11:00Clinical Applications of Deep Learning: Unboxing and DistillationHatem A. Rashwan
12:45Lunch break
14:00Metrics for AIK.Roitero (UNIUD)
16:00Teamwork: practical activities
Thursday 31st August, 2023
9:00Scientific dissemination: bibliometrics and altmetricsV.Della Mea
11:00Hyperparameter tuning techniquesL.Di Gaspero (UNIUD)
12:45Lunch break
14:00Integrated visualization of biomedical images (tentative title)A.Poli, T.Pace (O3 Enterprise)
15:15Teamwork: practical activities
Friday 1st September, 2023
9:00Federated LearningZouhair Haddi
11:00Privacy preserving ML-based modelsJosep Domingo Ferrer
12:45Lunch break
14:00Presentation of teamwork
15:30Final remarksV.Della Mea, D.Puig

Faculty

Laia Adalid – Pere Virgili Institute for Health Research (IISPV), Tarragona, Spain

Vincenzo Della Mea – University of Udine, Italy

Luca Di Gaspero – University of Udine, Italy

Carla Di Loreto – Azienda Ospedaliero-Universitaria, Udine, Italy

Josep Domingo Ferrer – Universitat Rovira iVirgili (URV), Tarragona, Spain

Zouhair Haddi – NVISION Systems and Technologies SL, Barcelona, Spain

Anna Korzynska – Nalecz Institute of Biocybernetics and Biomedical Engineering, Warszawa, Poland  

Alain Lalande – Université Bourgogne Franche-Comté, Bourgogne, France

Carlos Lopez – Pere Virgili Institute for Health Research (IISPV), Tarragona, Spain

Izidor Mlakar – University of Maribor, Maribor, Slovenia

Rodrigo Moreno – Royal Institute of Technology (KTH), Stockholm, Sweden

Teresa Pace – O3 Enterprise, Trieste, Italy

Enrico Pegolo – Azienda Ospedaliero-Universitaria, Udine, Italy

Andrea Poli – O3 Enterprise, Trieste, Italy

Domenec Puig – Universitat Rovira i Virgili (URV), Tarragona, Spain

Hatem A. Rashwan – Universitat Rovira i Virgili (URV), Tarragona, Spain

Kevin Roitero – University of Udine, Italy

Venue

Scuola Superiore dell’Università di Udine, Palazzo Di Toppo – Wassermann

Via Gemona 92, Udine, Italy

Organization

Medical Informatics, Telemedicine & e-Health Lab (MITEL), Dept. of Mathematics, Computer Science and Physics, University of Udine, Italy 

Institute of Pathology, Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), Udine, Italy

PhD Course in Computer Science & Artificial Intelligence
Dept. of Mathematics, Computer Science and Physics, University of Udine, Italy

On 11-12 May, 2023 the MSCA BosomShield Consortium is doing its first in presence meeting in Tarragona, Spain, at the University Rovira i Virgili. 10 Doctoral candidates, their supervisors, and other project partner will share their projects, with the ultimate goal of recognizing breast cancer relapse from radiological and pathological images and data by means of artificial intelligence.

bosomshield-logo

MITEL ranked in the winners group at the AGGC22 Challenge, during MICCAI 2022. Team members: Kevin Roitero, Vincenzo Della Mea.

aggc22

The European Society of Digital and Integrative Pathology (ESDIP) just published a paper on the implement Implementation of a Digital Pathology Workflow, with the participation of MITEL:

Fraggetta F, L’Imperio V, Ameisen D, Carvalho R, Leh S, Kiehl T-R, Serbanescu M, Racoceanu D, Della Mea V, Polonia A, Zerbe N, Eloy C. Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP). Diagnostics. 2021; 11(11):2167. https://doi.org/10.3390/diagnostics11112167

We decided to make public a dataset we used for a work some year ago (accelerometer data for daily activities): UNIUD Daily Activities Accelerometer Dataset (UNIUD-DA-AD).

Available at:

-Github:  https://github.com/MITEL-UNIUD/UNIUD-DA-AD

-Kaggle:  https://www.kaggle.com/vdellamea/uniud-daily-activities-accelerometer-dataset/ 

ESDIP Town Square Meeting
April 16, 2021 at 6 pm (CET)
“Can I trust AI in pathology?”

Dear All,

We are delighted to invite you to the ESDIP Town Square Meeting, a new series of informal events, starting on April 16, 2021, at 6:00 pm (CET) and aimed at promoting discussion around hot topics in digital and computational pathology.

Developed by the Educational Committee of ESDIP, under the supervision of Vincenzo Della Mea, from the University of Udine and Arvydas Laurinavičius from Vilnius University, this first meeting is titled “Can I trust AI in Pathology?”.




The main focus will be the role of artificial intelligence in pathology: the technology appears to be ready, but how reliable it is for the adoption in routine pathology practice?

The guests, Joe Saltz of the State University of New York at Stony Brook and Andrew Janowczyk of Case Western Reserve University, will briefly introduce their point of view about the title topic, then giving the floor to the public.

The valuable input from attendees, together with the expert views, will contribute to a better understanding of the advances as well as their possible clinical applications.

The workshop is free. You are welcome to attend, listen to the experts, and contribute with your viewpoint.To attend ESDIP Town Square Meeting, please send an email to 
admin@digitalpathologysociety.org until April 15, 2021. (Note: In case you have already submitted our registration and receive an email confirming it, please ignore this email). 

Sincerely,

Vincenzo Della Mea, Chair of the Educational Committee of ESDIP
On behalf of the Educational Committee of ESDIP

The last (open access) paper from our lab:

Underlying cause of death identification from death certificates using reverse coding to text and a NLP based deep learning approach

Vincenzo Della Mea, Mihai Horia Popescu, Kevin Roitero

Informatics in Medicine Unlocked, Volume 21, 2020, 100456

https://www.sciencedirect.com/science/article/pii/S2352914820306067

Our paper about the method that allowed us to reach the 2nd place in the HEROHE challenge is finally out:

La Barbera, D.; Polonia, A.; Roitero, K.; Econde-Sousa, E; Della Mea, V. Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning. J. Imaging 20206, 82.

https://www.mdpi.com/2313-433X/6/9/82