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PMID: 21788150 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

An accurate, fast and robust method to generate patient-specific cubic Hermite meshes.

Medical image analysis ·Vol. 15 ·No. 6 ·2011-12-00 ·Pages 801-13

Lamata P, Niederer S, Nordsletten D, Barber DC, Roy I, Hose DR, Smith N

Abstract

In-silico continuum simulations of organ and tissue scale physiology often require a discretisation or mesh of the solution domain. Cubic Hermite meshes provide a smooth representation of anatomy that is well-suited for simulating large deformation mechanics. Models of organ mechanics and deformation have demonstrated significant potential for clinical application. However, the production of a personalised mesh from patient's anatomy using medical images remains a major bottleneck in simulation workflows. To address this issue, we have developed an accurate, fast and automatic method for deriving patient-specific cubic Hermite meshes. The proposed solution customises a predefined template with a fast binary image registration step and a novel cubic Hermite mesh warping constructed using a variational technique. Image registration is used to retrieve the mapping field between the template mesh and the patient images. The variational warping technique then finds a smooth and accurate projection of this field into the basis functions of the mesh. Applying this methodology, cubic Hermite meshes are fitted to the binary description of shape with sub-voxel accuracy and within a few minutes, which is a significant advance over the existing state of the art methods. To demonstrate its clinical utility, a generic cubic Hermite heart biventricular model is personalised to the anatomy of four patients, and the resulting mechanical stability of these customised meshes is successfully demonstrated.

MeSH Terms
Biomechanical Phenomena Computational Biology/methods Computer Simulation Finite Element Analysis Heart/physiology Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional
Authors & Affiliations
7 authors, click to expand affiliations / ORCID
Lamata Pablo
University of Oxford, Computing Laboratory, Wolfson Building, Parks Road, OX1 3QD Oxford, UK.
Niederer Steven
Nordsletten David
Barber David C
Roy Ishani
Hose D Rod
Smith Nic
Article Info
Journal
Medical image analysis
Abbr.
Med Image Anal
ISSN
1361-8423
Published
2011-12-00
Epub
2011-00-06
Pages
801-13
Language
English
Region
Netherlands
NLM ID
9713490
Subset
IM
Analysis Services
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