Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching

Deformable surface mesh registration is a useful technique for various medical applications, such as intra-operative treatment guidance and intra- or inter-patient study. In this paper, we propose an automatic deformable mesh registration technique. The proposed method iteratively deforms a source mesh to a target mesh without manual feature extraction. Each iteration of the registration consists of two steps, automatic correspondence finding using robust point-matching (RPM) and local deformation using a radial basis function (RBF). The proposed RBF-based RPM algorithm solves the interlocking problems of correspondence and deformation using a deterministic annealing framework with fuzzy correspondence and RBF interpolation. Simulation tests showed promising results, with the average deviations decreasing by factors of 21.2 and 11.9, respectively. In the human model test, the average deviation decreased from 1.72±1.88mm to 0.57±0.66mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.

[1]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[2]  Stephen Breen,et al.  Biomechanical-based image registration for head and neck radiation treatment , 2010, Medical Imaging.

[3]  Amir A Zadpoor,et al.  Patient-specific finite element modeling of bones , 2013, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[4]  Zhengyou Zhang,et al.  Iterative point matching for registration of free-form curves and surfaces , 1994, International Journal of Computer Vision.

[5]  K. Brock,et al.  Demons deformable registration for CBCT-guided procedures in the head and neck: convergence and accuracy. , 2009, Medical physics.

[6]  William H. Press,et al.  Numerical Recipes 3rd Edition: The Art of Scientific Computing , 2007 .

[7]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[8]  Josien P. W. Pluim,et al.  Segmentation of Cervical Images by Inter-subject Registration with a Statistical Organ Model , 2011, Abdominal Imaging.

[9]  L. Joskowicz,et al.  Surface-based facial scan registration in neuronavigation procedures: a clinical study. , 2009, Journal of neurosurgery.

[10]  Dietmar W Hutmacher,et al.  Scaffold-based tissue engineering: rationale for computer-aided design and solid free-form fabrication systems. , 2004, Trends in biotechnology.

[11]  Steve B Jiang,et al.  Implementation and evaluation of various demons deformable image registration algorithms on a GPU. , 2010, Physics in medicine and biology.

[12]  Sébastien Ourselin,et al.  Fast free-form deformation using graphics processing units , 2010, Comput. Methods Programs Biomed..

[13]  D. Hill,et al.  Non-rigid image registration: theory and practice. , 2004, The British journal of radiology.

[14]  Gerald E. Farin,et al.  Image registration using hierarchical B-splines , 2004, IEEE Transactions on Visualization and Computer Graphics.

[15]  Baba C. Vemuri,et al.  Robust Point Set Registration Using Gaussian Mixture Models , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  Kunwoo Lee,et al.  3D virtual simulator for breast plastic surgery , 2008 .

[17]  Leonidas J. Guibas,et al.  Robust single-view geometry and motion reconstruction , 2009, ACM Trans. Graph..

[18]  Sandro Barone,et al.  Integration of 3D anatomical data obtained by CT imaging and 3D optical scanning for computer aided implant surgery , 2011, BMC Medical Imaging.

[19]  Eric Mjolsness,et al.  New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence , 1998, NIPS.

[20]  Alberto Signoroni,et al.  Deformable registration using patch-wise shape matching , 2014, Graph. Model..

[21]  Andriy Myronenko,et al.  Point Set Registration: Coherent Point Drift , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Richard K. Beatson,et al.  Reconstruction and representation of 3D objects with radial basis functions , 2001, SIGGRAPH.

[23]  Stephen Breen,et al.  Biomechanical-based image registration for head and neck radiation treatment. , 2010, Physics in medicine and biology.

[24]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[25]  Xia Li,et al.  Automatic nonrigid registration of whole body CT mice images. , 2008, Medical physics.

[26]  Anand Rangarajan,et al.  A new point matching algorithm for non-rigid registration , 2003, Comput. Vis. Image Underst..

[27]  Baowei Fei,et al.  Nonrigid point registration for 2D curves and 3D surfaces and its various applications , 2013, Physics in medicine and biology.

[28]  Sébastien Ourselin,et al.  Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for "dose of the day" calculations. , 2014, Medical physics.

[29]  Daniel Thalmann,et al.  Towards Effective Diagnosis and Prediction via 3D Patient Model: A Complete Research Plan , 2014, 3D Multiscale Physiological Human.

[30]  Sanford L Meeks,et al.  Clinical evaluation of interfractional variations for whole breast radiotherapy using 3-dimensional surface imaging. , 2013, Practical radiation oncology.

[31]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[32]  Joshua D. Lawson,et al.  Optically-guided frameless linac-based radiosurgery for brain metastases: clinical experience , 2009, Journal of Neuro-Oncology.

[33]  Maxime Sermesant,et al.  Application of soft tissue modelling to image-guided surgery. , 2005, Medical engineering & physics.