D
David Nordsletten
Researcher at University of Michigan
Publications - 130
Citations - 3145
David Nordsletten is an academic researcher from University of Michigan. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 28, co-authored 114 publications receiving 2337 citations. Previous affiliations of David Nordsletten include St Thomas' Hospital & University of Auckland.
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Journal ArticleDOI
Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.
Radomir Chabiniok,Radomir Chabiniok,Vicky Y. Wang,Myrianthi Hadjicharalambous,Liya Asner,Jack Lee,Maxime Sermesant,Ellen Kuhl,Alistair A. Young,Philippe Moireau,Martyn P. Nash,Dominique Chapelle,David Nordsletten +12 more
TL;DR: Developments in computational cardiac modelling are reviewed and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.
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Coupling multi-physics models to cardiac mechanics.
TL;DR: An arbitrary Eulerian-Lagrangian framework governing the behaviour of both fluid and solid components is introduced and the potential of cardiac mechanics modelling for clinical applications is discussed.
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Structural morphology of renal vasculature
TL;DR: An automatic segmentation technique has been developed and applied to two renal micro-computer tomography images, providing convincing evidence of the "minimum work" hypothesis.
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euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling
Nic Smith,Nic Smith,Adelaide de Vecchi,Matt McCormick,David Nordsletten,Oscar Camara,Alejandro F. Frangi,Alejandro F. Frangi,Hervé Delingette,Maxime Sermesant,Jatin Relan,Nicholas Ayache,Martin W. Krueger,Walther H. W. Schulze,Rod Hose,Israel Valverde,Philipp Beerbaum,Cristina Staicu,Maria Siebes,Jos A. E. Spaan,Peter Hunter,Juergen Weese,Helko Lehmann,Dominique Chapelle,Reza Rezavi +24 more
TL;DR: In this paper, the authors integrate multiple types of functional data into a consistent framework using multi-scale computational modelling to address the issue of contradictory treatments plans owing to inter-individual variability in pathophysiology.
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An accurate, fast and robust method to generate patient-specific cubic Hermite meshes
Pablo Lamata,Pablo Lamata,Steven A. Niederer,Steven A. Niederer,David Nordsletten,David Nordsletten,David Charles Barber,Ishani Roy,Ishani Roy,R. Hose,Nic Smith,Nic Smith +11 more
TL;DR: An accurate, fast and automatic method for deriving patient-specific cubic Hermite meshes from patient's anatomy using medical images is developed, and the resulting mechanical stability of these customised meshes is successfully demonstrated.