Explicit Incorporation of Prior Anatomical Information Into a Nonrigid Registration of Thoracic and Abdominal CT and 18-FDG Whole-Body Emission PET Images

The aim of this paper is to develop a registration methodology in order to combine anatomical and functional information provided by thoracic/abdominal computed tomography (CT) and whole-body positron emission tomography (PET) images. The proposed procedure is based on the incorporation of prior anatomical information in an intensity-based nonrigid registration algorithm. This incorporation is achieved in an explicit way, initializing the intensity-based registration stage with the solution obtained by a nonrigid registration of corresponding anatomical structures. A segmentation algorithm based on a hierarchically ordered set of anatomy-specific rules is used to obtain anatomical structures in CT and emission PET scans. Nonrigid deformations are modeled in both registration stages by means of free-form deformations, the optimization of the control points being achieved by means of an original vector field-based approach instead of the classical gradient-based techniques, considerably reducing the computational time of the structure registration stage. We have applied the proposed methodology to 38 sets of images (33 provided by standalone machines and five by hybrid systems) and an assessment protocol has been developed to furnish a qualitative evaluation of the algorithm performance

[1]  R. Wahl,et al.  "Anatometabolic" tumor imaging: fusion of FDG PET with CT or MRI to localize foci of increased activity. , 1993, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[2]  Torsten Rohlfing,et al.  Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees , 2003, IEEE Transactions on Information Technology in Biomedicine.

[3]  Jerry L. Prince,et al.  Generalized gradient vector flow external forces for active contours , 1998, Signal Process..

[4]  Cyrill Burger,et al.  PET-CT image co-registration in the thorax: influence of respiration , 2002, European Journal of Nuclear Medicine and Molecular Imaging.

[5]  M. J. D. Powell,et al.  An efficient method for finding the minimum of a function of several variables without calculating derivatives , 1964, Comput. J..

[6]  Daniel Rueckert,et al.  Building a 4D atlas of the cardiac anatomy and motion using MR imaging , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[7]  David W Townsend,et al.  PET/CT today and tomorrow. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[8]  H N Wagner SNM 1999. Fused image tomography: an integrating force. , 1999, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[9]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[10]  I. Bloch,et al.  Non-linear Registration Between 3 D Images Including Rigid Objects : Application to CT and PET Lung Images With Tumors , 2006 .

[11]  Charles R. Meyer,et al.  Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations , 1997, Medical Image Anal..

[12]  Alejandro F Frangi,et al.  Automatic construction of 3-D statistical deformation models of the brain using nonrigid registration , 2003, IEEE Transactions on Medical Imaging.

[13]  Morten Bro-Nielsen,et al.  Fast Fluid Registration of Medical Images , 1996, VBC.

[14]  David R. Haynor,et al.  PET-CT image registration in the chest using free-form deformations , 2003, IEEE Transactions on Medical Imaging.

[15]  Yuji Nakamoto,et al.  Respiratory motion artifacts on PET emission images obtained using CT attenuation correction on PET-CT , 2003, European Journal of Nuclear Medicine and Molecular Imaging.

[16]  Sun I. Kim,et al.  Intensity based affine registration including feature similarity for spatial normalization , 2002, Comput. Biol. Medicine.

[17]  Thomas Beyer,et al.  The SMART scanner: a combined PET/CT tomograph for clinical oncology , 1998, 1998 IEEE Nuclear Science Symposium Conference Record. 1998 IEEE Nuclear Science Symposium and Medical Imaging Conference (Cat. No.98CH36255).

[18]  B.M.W. Tsui,et al.  Study of the efficacy of respiratory gating in myocardial SPECT using the new 4D NCAT phantom , 2001, 2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310).

[19]  Isabelle Bloch,et al.  Description of brain internal structures by means of spatial relations for MR image segmentation , 2004, SPIE Medical Imaging.

[20]  David J. Hawkes,et al.  Validation of nonrigid image registration using finite-element methods: application to breast MR images , 2003, IEEE Transactions on Medical Imaging.

[21]  Heinrich Müller,et al.  Image warping with scattered data interpolation , 1995, IEEE Computer Graphics and Applications.

[22]  Raj Shekhar,et al.  Automated 3D Elastic Registration for Improving Tumor Localization in Whole-body PET-CT from Combined Scanner , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  Paul Kinahan,et al.  A combined PET/CT scanner for clinical oncology. , 2000, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[24]  C A Pelizzari,et al.  Intermodality, retrospective image registration in the thorax. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[25]  Guy Marchal,et al.  Clinical relevance of an automated algorithm for multi-modality image registration based on maximization of mutual information , 1997 .

[26]  Damini Dey,et al.  Automated 3-dimensional registration of stand-alone (18)F-FDG whole-body PET with CT. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[27]  James C. Gee,et al.  Finite element approach to warping of brain images , 1994, Medical Imaging.

[28]  Lawrence H. Staib,et al.  Physical model-based non-rigid registration incorporating statistical shape information , 2000, Medical Image Anal..

[29]  J. Chu,et al.  CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching method. , 1999, International journal of radiation oncology, biology, physics.

[30]  Daniel Rueckert,et al.  A Framework for Detailed Objective Comparison of Non-rigid Registration Algorithms in Neuroimaging , 2004, MICCAI.

[31]  Nicholas Ayache,et al.  Iconic feature based nonrigid registration: the PASHA algorithm , 2003, Comput. Vis. Image Underst..

[32]  Dinggang Shen,et al.  Deformable registration of cortical structures via hybrid volumetric and surface warping , 2004, NeuroImage.

[33]  Johan Montagnat,et al.  Modèles déformables pour la segmentation et la modélisation d'images médicales 3D et 4D , 1999 .

[34]  W. Segars,et al.  Study of the efficacy of respiratory gating in myocardial SPECT using the new 4-D NCAT phantom , 2001 .

[35]  Oscar Camara-Rey Non-linear registration of thoracic and abdominal CT and 18-FDG whole-body emission PET images: methodological study and application in clinical routine , 2003 .

[36]  Masayuki Nakajima,et al.  Nonlinear registration of medical images using Cauchy-Navier spline transformation , 1999, Medical Imaging.

[37]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[38]  R. Shekhar,et al.  Automated 3-dimensional elastic registration of whole-body PET and CT from separate or combined scanners. , 2005, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[39]  Yuji Nakamoto,et al.  Clinically significant inaccurate localization of lesions with PET/CT: frequency in 300 patients. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[40]  Thomas W. Sederberg,et al.  Free-form deformation of solid geometric models , 1986, SIGGRAPH.

[41]  K M Ayyangar,et al.  Clinical fusion of three-dimensional images using Bremsstrahlung SPECT and CT. , 1997, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[42]  Paul Suetens,et al.  A Viscous Fluid Model for Multimodal Non-rigid Image Registration Using Mutual Information , 2002, MICCAI.

[43]  Pierre Hellier,et al.  Coupling dense and landmark-based approaches for nonrigid registration , 2003, IEEE Transactions on Medical Imaging.

[44]  Simon R. Arridge,et al.  A survey of hierarchical non-linear medical image registration , 1999, Pattern Recognit..

[45]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[46]  William Paul Segars,et al.  Development of a new dynamic NURBS-based cardiac-torso (NCAT) phantom , 2001 .

[47]  L. Thurfjell,et al.  Image registration: an essential tool for nuclear medicine , 2002, European Journal of Nuclear Medicine and Molecular Imaging.

[48]  John L. Humm,et al.  Radiotherapy treatment planning for patients with non-small cell lung cancer using positron emission tomography (PET). , 2002, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

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

[50]  Michael I. Miller,et al.  Individualizing Neuroanatomic Atlases Using a Massively Parallel Computer , 1996, Computer.

[51]  Jan Flusser,et al.  Image registration methods: a survey , 2003, Image Vis. Comput..

[52]  Stephen Marsland,et al.  Clamped-Plate Splines and the Optimal Flow of Bounded Diffeomorphisms , 2002 .

[53]  Oscar Camara,et al.  Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis , 2006, IEEE Transactions on Medical Imaging.

[54]  Isabelle Bloch,et al.  Computational modeling of thoracic and abdominal anatomy using spatial relationships for image segmentation , 2004, Real Time Imaging.

[55]  E. Hoffman,et al.  Utilization of 3-D elastic transformation in the registration of chest X-ray CT and whole body PET , 1996 .

[56]  Isabelle Bloch,et al.  Free Form Deformations Guided by Gradient Vector Flow: A Surface Registration Method in Thoracic and Abdominal PET-CT Applications , 2003, WBIR.

[57]  Alejandro F. Frangi,et al.  Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling , 2002, IEEE Transactions on Medical Imaging.

[58]  D. Hill,et al.  Medical image registration , 2001, Physics in medicine and biology.

[59]  Nira Dyn,et al.  Image Warping by Radial Basis Functions: Application to Facial Expressions , 1994, CVGIP Graph. Model. Image Process..

[60]  H Lester Non-linear registration of medical images. , 1999 .