title: Biomechanical model for computing deformations for whole-body image registration: A meshless approach.
abstract: Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time-consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2D models and computing single organ deformations. In this study, 3D comprehensive patient-specific nonlinear biomechanical models implemented using meshless Total Lagrangian explicit dynamics algorithms are applied to predict a 3D deformation field for whole-body image registration. Unlike a conventional approach that requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the fuzzy c-means algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia.
authors.forename: Mao
authors.initials: M
authors.lastname: Li
authors.affiliation: Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia.|Institute of Mechanics and Advanced Materials, Cardiff School of Engineering, Cardiff University, Wales, UK.
authors.forename: Karol
authors.initials: K
authors.lastname: Miller
authors.affiliation: Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia.
authors.forename: Grand Roman
authors.initials: GR
authors.lastname: Joldes
authors.affiliation: Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.|Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany.
authors.forename: Ron
authors.initials: R
authors.lastname: Kikinis
authors.affiliation: Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia.
authors.forename: Adam
authors.initials: A
authors.lastname: Wittek
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed; D051598:Whole Body Imaging / Q000379:methods*
keywords: Hausdorff distance; meshless methods; meshless model; patient-specific biomechanical modelling; whole-body image registration