Conference Agenda

Overview and session details of the ESB2023 congress.
Please select a date or location to view only sessions for that date or location. Please select an individual session for a detailed view (with abstracts where available).
Please select a "List View" option to access presentation abstracts directly from this page.

 
 
Session Overview
Session
AI / Data-driven modelling in biomechanics IV: Cardiovascular System
Time:
Wednesday, 12/July/2023:
17:00 - 18:15

Session Chair: Mirunalini Thirugnanasambandam
Session Chair: Simona Celi
Location: Copenhagen (Room 0.3)


Show help for 'Increase or decrease the abstract text size'
Presentations
17:00 - 17:12
ID: 645

DATA-DRIVEN FSI SIMULATION OF VENTRICLE AND AORTA INTEGRATING IN VIVO AND IN SILICO DATA

M. A. Scarpolini1,2, G. Piumini3, F. Cademartiri4, S. Celi1, F. Viola5

1BioCardioLab, Fondazione Toscana Gabriele Monasterio, Italy; 2University of Rome “Tor Vergata”, Italy; 3University of Twente, The Netherlands; 4Clinical Imaging Department, Fondazione Toscana Gabriele Monasterio, Italy; 5GSSI (Gran Sasso Science Institute), L’Aquila, Italy

ESB2023_3.4_Scarpolini_645_abstract.pdf


17:12 - 17:24
ID: 465

A CT-BASED DEEP LEARNING SYSTEM FOR AUTOMATIC ASSESSMENT OF AORTIC ROOT MORPHOLOGY FOR TAVI PLANNING

S. Saitta1, F. Sturla2,1, R. Gorla2, O. Oliva2, E. Votta1,2, F. Bedogni2, A. Redaelli1

1Politecnico di Milano, Italy; 2IRCCS Policlinico San Donato, Italy

ESB2023_3.4_Saitta_465_abstract.pdf


17:24 - 17:36
ID: 716

DATA-DRIVEN METHODS FOR PATIENT-SPECIFIC REDUCED ORDER MODELING OF COMPLEX AORTIC FLOWS

C. Chatpattanasiri1,2, G. Franzetti1, V. Diaz-Zuccarini1,2, S. Balabani1,2

1Department of Mechanical Engineering, University College London, London, UK; 2Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), Department of Medical Physics and Biomedical Engineering, University College London, London, UK

ESB2023_3.4_Chatpattanasiri_716.pdf


17:36 - 17:48
ID: 853

AORTIC SEGMENTATION VIA SYNTHETIC DATA AUGMENTATION STRATEGY FROM PC-MRI SMALL DATASET

S. Garzia1,2, M. A. Scarpolini1,3, M. Mazzoli1,2, A. Monteleone4, F. Cademartiri4, S. Celi1

1BioCardioLab - Fondazione Toscana Gabriele Monasterio, Italy; 2Department of Information Engineering, University of Pisa, Italy; 3Department of Industrial Engineering, University of Rome "Tor Vergata", Italy; 4Clinical Imaging Department, Fondazione Toscana Gabriele Monasterio, Italy

ESB2023_3.4_Garzia_853.pdf


17:48 - 18:00
ID: 898

DEEP RESIDUAL AMBIVALENT GRAPH CONVOLUTIONAL NETWORKS FOR BIOMARKER PREDICTION IN LARGE VESSEL NETWORKS

A. B. Drysdale1, H. Arora1, A. Davies2, R. van Loon1

1Swansea University, United Kingdom; 2United Kingdom Atom Energy Authority, Culham Centre for Fusion Energy

ESB2023_3.4_Drysdale_898.pdf


18:00 - 18:12
ID: 653

IMPLEMENTING DIGITAL TWINS OF THE CARDIOVASCULAR SYSTEM IN CLINICAL SETTINGS: AN AUTOMATED DEEP LEARNING PIPELINE

M. A. Scarpolini1,2, M. Mazzoli1,3, S. Garzia1,3, A. Monteleone4, S. Celi1

1BioCardioLab, Fondazione Toscana Gabriele Monasterio, Italy; 2University of Rome “Tor Vergata”, Italy; 3Department of Information Engineering, University of Pisa, Italy; 4Clinical Imaging Department, Fondazione Toscana Gabriele Monasterio, Italy

ESB2023_3.4_Scarpolini_653.pdf


 
Contact and Legal Notice · Contact Address:
Privacy Statement · Conference: ESB 2023
Conference Software: ConfTool Pro 2.8.101+TC
© 2001–2024 by Dr. H. Weinreich, Hamburg, Germany