title: Patient-specific biomechanical model as whole-body CT image registration tool.
abstract: Whole-body computed tomography (CT) image registration is important for cancer diagnosis, therapy planning and treatment. Such registration requires accounting for large differences between source and target images caused by deformations of soft organs/tissues and articulated motion of skeletal structures. The registration algorithms relying solely on image processing methods exhibit deficiencies in accounting for such deformations and motion. We propose to predict the deformations and movements of body organs/tissues and skeletal structures for whole-body CT image registration using patient-specific non-linear biomechanical modelling. Unlike the conventional biomechanical modelling, our approach for building the biomechanical models does not require time-consuming segmentation of CT scans to divide the whole body into non-overlapping constituents with different material properties. Instead, a Fuzzy C-Means (FCM) algorithm is used for tissue classification to assign the constitutive properties automatically at integration points of the computation grid. We use only very simple segmentation of the spine when determining vertebrae displacements to define loading for biomechanical models. We demonstrate the feasibility and accuracy of our approach on CT images of seven patients suffering from cancer and aortic disease. The results confirm that accurate whole-body CT image registration can be achieved using a patient-specific non-linear biomechanical model constructed without time-consuming segmentation of the whole-body images.
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, Cardiff, 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: Vascular Engineering, Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia; Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK.
authors.forename: Barry
authors.initials: B
authors.lastname: Doyle
authors.affiliation: Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Crawley, Perth, Australia.
authors.forename: Revanth Reddy
authors.initials: RR
authors.lastname: Garlapati
authors.affiliation: Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Fraunhofer MEVIS, Bremen, Germany; Professor für Medical Image Computing, MZH, University of Bremen, 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. Electronic address: adam.wittek@uwa.edu.au.
authors.forename: Adam
authors.initials: A
authors.lastname: Wittek
mesh_terms: D000465:Algorithms; D005240:Feasibility Studies; D020342:Finite Element Analysis; D017143:Fuzzy Logic; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D066230:Patient-Specific Modeling; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*; D051598:Whole Body Imaging / Q000379:methods*
keywords: Fuzzy-C Means; Hausdorff distance; Non-linear finite element analysis; Patient-specific biomechanical model; Whole-body image registration