Conference Agenda

THREE-DIMENSIONAL OSTEOCYTE LACUNO-CANALICULAR NETWORK AT THE BONE IMPLANT INTERFACE

K. Abouzaid¹, T. Reiss², H. Albini-Lomami¹, G. Haïat¹, E. Vennat², S. Le Cann¹

¹CNRS, MSME UMR 8208, France; ²Université Paris-Saclay, CentraleSupélec, ENS Paris-Saclay, CNRS, LMPS, France

A CONTRAST-ENHANCED X-RAY IMAGING APPROACH FOR CHARACTERIZING ARTICULAR CARTILAGE

S. Fantoni¹, M. Berni², M. Assenza², P. Cardarelli³, A. Taibi⁴, C. Trapella⁵, V. Cristofori⁵, F. Baruffaldi², N. F. Lopomo⁶, M. Baleani²

¹Department of Industrial Engineering, University of Bologna, Italy; ²Medical Technology Laboratory, IRCCS Istituto Ortopedico Rizzoli, Italy; ³Istituto Nazionale di Fisica Nucleare (INFN), Division of Ferrara, Italy; ⁴Department of Physics and Earth Sciences, University of Ferrara, Italy; ⁵Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Italy; ⁶Department of Information Engineering, University of Brescia, Italy

4D CT AS A TOOL TO MEASURE SCAPHOLUNATE DISTANCE: AN INTRA-AND INTEROBSERVER EVALUATION

S. Goeminne¹, E. Salaets¹, W. Coudyzer¹, D. Shah², I. Degreef¹, L. Scheys¹

¹KULeuven, Belgium; ²ITT, India

MUSCLE DIFFUSION TENSOR IMAGING: INFLUENCE OF SEGMENTATION ON THE DETERMINATION OF MUSCLE ARCHITECTURE

S. Vetter¹, H.-P. Köhler¹, M. Witt¹, J. Henkelmann², C. Roth²

¹Leipzig University, Germany; ²Universitätsklinikum Leipzig, Germany

NEURAL RADIANCE FIELDS FOR VESSEL RECONSTRUCTION FROM 2D X-RAY CORONARY ANGIOGRAPHY PROJECTIONS – PROOF OF CONCEPT

A. J. E. Vermeer^1,2, K. W. H. Maas³, P.-J.J. Vlaar², F. N. Vosse¹, M. van 't Veer^1,2

¹Department of Biomedical Engineering, Eindhoven University of Technology; ²Department of Cardiology, Catharina Hospital Eindhoven; ³Department of Mathematics and Computer Science, Eindhoven University of Technology

CORONARY ARTERY SEGMENTATION IN HYPEREMIA CONDITIONS FOR COMPUTED FFR ANALYSIS

J. Festas^1,2, L. C. Sousa^1,2, C. C. António^1,2, S. Silva³, S. I. Pinto^1,2

¹Engineering Faculty, University of Porto, Porto, Portugal; ²Institute of Science and Innovation in Mechanical and Industrial Engineering (LAETA-INEGI), Porto, Portugal; ³Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, Aveiro, Portugal

DEEP LEARNING THORACIC AORTA SEGMENTATION FOR FEATURE EXTRACTION AND HEMODYNAMIC ANALYSIS FROM 3D PC-MRI

S. Garzia^1,2, M. A. Scarpolini^1,3, K. Capellini¹, V. Positano¹, 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", Roma, Italy; ⁴Clinical Imaging Department, Fondazione Toscana Gabriele Monasterio, Italy