A multiscale phase field method for joint segmentation-rigid registration application to motion estimation of human knee joint

Eslami, A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1142/S1016237211002839
  3. Publisher: 2011
  4. Abstract:
  5. Image based registration of rigid objects has been frequently addressed in the literature to obtain an object's motion parameters. In this paper, a new approach of joint segmentation-rigid registration, within the variational framework of the phase field approximation of the Mumford-Shah's functional, is proposed. The defined functional consists of two Mumford-Shah equations, extracting the discontinuity set of the reference and target images due to a rigid spatial transformation. Multiscale minimization of the proposed functional after finite element discretization provided a sub-pixel, robust algorithm for edge extraction as well as edge based rigid registration. The implementation considerations of the proposed method, including memory usage, convergence rate and effects of parameters selection, was discussed and its efficacy was examined in a comprehensive set of synthetic, phantom and clinical experiments. It was found that the proposed joint segmentation-rigid registration method provides improved results, in comparison with the currently available methods which are often based on maximizing images similarities, especially when the reference and target images are of different qualities. A high registration accuracy was obtained when estimating the knee joint kinematics through MR images taken at different joint configurations. It was concluded that the proposed method can be effectively used in applications where 3D image registration of rigid objects is concerned, e.g. for estimation of the motion parameters of human joints
  6. Keywords:
  7. Human Joint Kinematics ; Joint tasks processing ; Phase field approximation ; Sub-pixel registration ; Sub-pixel segmentation ; 3D image registration ; Convergence rates ; Edge extraction ; Edge-based ; Finite-element discretization ; Human joints ; Human knee joint ; Image-based ; Joint configuration ; Knee joint kinematics ; Memory usage ; Motion parameters ; MR images ; Multiscales ; Mumford-Shah ; Mumford-Shah functional ; Parameters selection ; Phase field methods ; Phase fields ; Registration accuracy ; Registration methods ; Rigid objects ; Rigid registration ; Robust algorithm ; Spatial transformation ; Sub pixels ; Target images ; Variational framework ; Estimation ; Image segmentation ; Kinematics ; Motion estimation ; Parameter estimation ; Physiological models ; Pixels ; Three dimensional ; Joints (anatomy) ; Algorithm ; Biomechanics ; Image processing ; Image quality ; Joint segmentation rigid registration ; Knee ; Mathematical parameters ; Mumford Shah equation ; Nuclear magnetic resonance ; Range of motion ; Signal noise ratio ; Simulation ; Three dimensional imaging
  8. Source: Biomedical Engineering - Applications, Basis and Communications ; Volume 23, Issue 6 , 2011 , Pages 445-456 ; 10162372 (ISSN)
  9. URL: http://www.worldscientific.com/doi/abs/10.4015/S1016237211002839