Classification of glenoid bone loss patterns using statistical shape modelling

Harnoor Saini¹, Julie Kim¹, Marc Hirner², Sumit Raniga³, Desmond Bokor³, Thor Besier¹

¹Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; ²Northland Orthopaedic Clinic, Whangarei, New Zealand; ³Shoulder and Elbow Clinic, Macquarie University, Sydney, NSW, Australia

Strain analysis in the right ventricular outflow tract using non-parametric deformable shape modelling

Liam David Swanson^1,2, Raphael Sivera^1,2, Nicholas M. Jacobson³, Claudio Capelli^1,2, Catalina Vargas-Acevedo^4,5, Gareth J. Morgan^5,6,7, Silvia Schievano^1,2

¹Institute of Cardiovascular Sciences, University College London, London, United Kingdom; ²Great Ormond Street Children’s Hospital, London, United Kingdom; ³College of Engineering, Design and Computing, University of Colorado, Aurora, CO, United States of America; ⁴Department of Pediatric Cardiology, University of Colorado, Aurora, CO, United States of America; ⁵The Heart Institute, Children's Hospital Colorado, Aurora, CO, United States of America; ⁶School of Medicine, Anschutz Medical Campus, University of Colorado, Aurora, CO, United States of America; ⁷Department of Cardiology, University of Colorado Hospital, Aurora, CO, United States of America

Hexahedral mesh fitting using scaffolds and statistical shape modelling to reproduce the cortical bone morphology of the femur

Ted Yeung, Thor Besier, Peter Hunter, Vickie Shim

Auckland Bioengineering Institute, University of Auckland, New Zealand

Development of a statistical shape and density model of the paediatric femur for personalised FE models in children

Yidan Xu, Laura Carman, Thor Besier, Julie Choisne

Auckland Bioengineering Institute, The University of Auckland, New Zealand

Generation of digital genetic twins satisfying utility and privacy metrics for robust post-hoc analyses

Igor Faddeenkov¹, Olivia Rousseau¹, Sonia Bourguiba-Hachemi¹, Sophie Limou^1,2, Nicolas Vince¹, Pierre-Antoine Gourraud^1,3

¹Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, F-44000 Nantes, France; ²Ecole Centrale de Nantes, F-44300 Nantes, France; ³Nantes Université, CHU Nantes, PHU¹¹Santé Publique, Clinique des données, INSERM CIC 1413, F-44000 Nantes, France

Domain adaptation methods for emotion and pain recognition via synthetic data

Jonas Nasimzada¹, Constantin Seibold², Alina Roitberg¹

¹University of Stuttgart, Germany; ²University Medicine Essen, Germany