Technology and research developments in carotid image registration

Abstract Brain stroke is the leading cause of death worldwide. Mortality, morbidity and economic effects of stroke are alarming. Carotid atherosclerosis is the most common cause of stroke. Early identification, monitoring and quantification of carotid plaque with the help of imaging modalities can help manage the stroke and evaluate the effectiveness of medical therapy. Carotid image registration has the potential to improve the monitoring, quantification and characterization of the disease. It helps to accurately correlate the findings of various imaging modalities for the diagnostic and therapeutic purposes. This paper aims to present the current state-of-the-art in carotid image registration techniques. For the monomodality registration, ultrasound and magnetic resonance imaging are the primary concerns. Multimodality registration will cover the combination of different modalities. The registration process and validation methods for carotid image registration are also discussed.

[1]  Robert F Mattrey,et al.  Carotid arteries: contrast-enhanced US angiography--preliminary clinical experience. , 2004, Radiology.

[2]  Isaac N. Bankman,et al.  Handbook of medical image processing and analysis , 2009 .

[3]  Tom Vercauteren,et al.  Diffeomorphic demons: Efficient non-parametric image registration , 2009, NeuroImage.

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

[5]  John David Spence,et al.  A Non-Rigid Image Registration Technique for 3D Ultrasound Carotid Images using a "Twisting and Bending" Model , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.

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

[7]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

[8]  Jürgen Weese,et al.  Landmark-based elastic registration using approximating thin-plate splines , 2001, IEEE Transactions on Medical Imaging.

[9]  A D Hughes,et al.  Carotid geometry reconstruction: a comparison between MRI and ultrasound. , 2003, Medical physics.

[10]  Aaron Fenster,et al.  3D Ultrasound Measurement of Change in Carotid Plaque Volume: A Tool for Rapid Evaluation of New Therapies , 2005, Stroke.

[11]  V. Fuster,et al.  Atherosclerosis: imaging techniques and the evolving role of nuclear medicine. , 1997, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[12]  G. Schroth,et al.  Contrast-enhanced 3D MR angiography of the carotid artery: comparison with conventional digital subtraction angiography. , 2002, AJNR. American journal of neuroradiology.

[13]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[14]  D. Louis Collins,et al.  Cortical Constraints for Non-Linear Cortical Registration , 1996, VBC.

[15]  John David Spence,et al.  A “Twisting and Bending” Model-Based Nonrigid Image Registration Technique for 3-D Ultrasound Carotid Images , 2008, IEEE Transactions on Medical Imaging.

[16]  Nathan D. Cahill,et al.  Fourier Methods for Nonparametric Image Registration , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  Patrick Clarysse,et al.  A review of cardiac image registration methods , 2002, IEEE Transactions on Medical Imaging.

[18]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[19]  C Yuan,et al.  Carotid atherosclerotic plaque: noninvasive MR characterization and identification of vulnerable lesions. , 2001, Radiology.

[20]  M W Vannier,et al.  Image-based dose planning of intracavitary brachytherapy: registration of serial-imaging studies using deformable anatomic templates. , 2001, International journal of radiation oncology, biology, physics.

[21]  Ruzena Bajcsy,et al.  Multiresolution elastic matching , 1989, Comput. Vis. Graph. Image Process..

[22]  P. Dalal Burden of Stroke: Indian Perspective , 2004, International journal of stroke : official journal of the International Stroke Society.

[23]  Jean-Francois Mangin,et al.  Multisubject Non-rigid Registration of Brain MRI Using Intensity and Geometric Features , 2001, MICCAI.

[24]  Karl Rohr,et al.  Radial basis functions with compact support for elastic registration of medical images , 2001, Image Vis. Comput..

[25]  R. Woods,et al.  Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain , 2000, Human brain mapping.

[26]  Ben Glocker,et al.  Simultaneous Geometric - Iconic Registration , 2010, MICCAI.

[27]  Y. Bentoutou,et al.  An invariant approach for image registration in digital subtraction angiography , 2002, Pattern Recognit..

[28]  Jan Modersitzki,et al.  Numerical Methods for Image Registration , 2004 .

[29]  A. Toga,et al.  Detection and mapping of abnormal brain structure with a probabilistic atlas of cortical surfaces. , 1997, Journal of computer assisted tomography.

[30]  Jean-Philippe Thirion,et al.  Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..

[31]  C Yuan,et al.  Comparison of carotid vessel wall area measurements using three different contrast-weighted black blood MR imaging techniques. , 2001, Magnetic resonance imaging.

[32]  Y. Chan,et al.  Blood flow volume quantification of cerebral ischemia: comparison of three noninvasive imaging techniques of carotid and vertebral arteries. , 2002, AJR. American journal of roentgenology.

[33]  J. Waterton,et al.  Volumetric assessment of carotid artery bifurcation using freehand-acquired, compound 3D ultrasound. , 1999, The British journal of radiology.

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

[35]  J. Gillard,et al.  Multi-sequence in vivo MRI can quantify fibrous cap and lipid core components in human carotid atherosclerotic plaques. , 2004, European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery.

[36]  T. Banerjee,et al.  Epidemiology of stroke in India , 2006 .

[37]  M. Powell A View of Algorithms for Optimization without Derivatives 1 , 2007 .

[38]  Aaron Fenster,et al.  3D ultrasound imaging of the carotid arteries. , 2004, Current drug targets. Cardiovascular & haematological disorders.

[39]  H. Diener,et al.  Quantification of atherosclerotic plaques in carotid arteries by three-dimensional ultrasound. , 1994, The British journal of radiology.

[40]  Karl J. Friston,et al.  Rigid Body Registration , 2003 .

[41]  A Fenster,et al.  Evaluation of voxel-based registration of 3-D power Doppler ultrasound and 3-D magnetic resonance angiographic images of carotid arteries. , 2001, Ultrasound in medicine & biology.

[42]  C. Yuan,et al.  Visualization of Fibrous Cap Thickness and Rupture in Human Atherosclerotic Carotid Plaque In Vivo With High-Resolution Magnetic Resonance Imaging , 2000, Circulation.

[43]  D. Strandness,et al.  Ultrasonic Evaluation of the Carotid Bifurcation , 1987 .

[44]  V. Fuster,et al.  Clinical Imaging of the High-Risk or Vulnerable Atherosclerotic Plaque , 2001, Circulation research.

[45]  R. Mohan,et al.  Motion adaptive x-ray therapy: a feasibility study , 2001, Physics in medicine and biology.

[46]  Jonathan S. Lewin,et al.  Three-dimensional automatic volume registration of carotid MR images , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[47]  A. Fenster,et al.  3-D ultrasound imaging: a review , 1996 .

[48]  Mark Holden,et al.  A Review of Geometric Transformations for Nonrigid Body Registration , 2008, IEEE Transactions on Medical Imaging.

[49]  Pierre Hellier,et al.  Hierarchical estimation of a dense deformation field for 3-D robust registration , 2001, IEEE Transactions on Medical Imaging.

[50]  Sven Kabus,et al.  B-spline registration of 3D images with Levenberg-Marquardt optimization , 2004, SPIE Medical Imaging.

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

[53]  Praful Dalal,et al.  UN millennium development goals: Can we halt the stroke epidemic in India? , 2007 .

[54]  Gary Friday,et al.  2011 ASA/ACCF/AHA/AANN/AANS/ACR/ASNR/CNS/SAIP/SCAI/SIR/SNIS/SVM/SVS guideline on the management of patients with extracranial carotid and vertebral artery disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American , 2011, Journal of the American College of Cardiology.

[55]  Volker Rasche,et al.  Non-rigid registration for fusion of carotid vascular ultrasound and MRI volumetric datasets , 2006, SPIE Medical Imaging.

[56]  Christof Karmonik,et al.  Quantitative Segmentation of Principal Carotid Atherosclerotic Lesion Components by Feature Space Analysis Based on Multicontrast MRI at 1.5 T , 2009, IEEE Transactions on Biomedical Engineering.

[57]  Gary Friday,et al.  2011 ASA/ACCF/AHA/AANN/AANS/ACR/ASNR/CNS/SAIP/SCAI/SIR/SNIS/SVM/SVS guideline on the management of patients with extracranial carotid and vertebral artery disease. , 2011, Stroke.

[58]  Piotr J. Slomka,et al.  Automated 3D registration of magnetic resonance angiography, 3D power doppler, and 3D B-mode ultrasound images of carotid bifurcation , 2000, Medical Imaging: Image Processing.

[59]  X. Y. Xu,et al.  Ultrasound image-based computer model of a common carotid artery with a plaque. , 2004, Medical engineering & physics.

[60]  Kawal S. Rhode,et al.  Tissue deformation and shape models in image-guided interventions: a discussion paper , 2005, Medical Image Anal..

[61]  Paul M. Thompson,et al.  The role of image registration in brain mapping , 2001, Image Vis. Comput..

[62]  B. Solaiman,et al.  Validation of calibration by spatial registration between US and MRI scans: Application to carotid of bifurcation , 2008, 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications.

[63]  Nathan D. Cahill,et al.  A Demons Algorithm for Image Registration with Locally Adaptive Regularization , 2009, MICCAI.

[64]  J. Suri,et al.  An Integrated Approach to Computer‐Based Automated Tracing and Its Validation for 200 Common Carotid Arterial Wall Ultrasound Images , 2010, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[65]  Josien P. W. Pluim,et al.  Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines , 2007, IEEE Transactions on Image Processing.

[66]  Alfons G H Kessels,et al.  Assessment of human atherosclerotic carotid plaque components with multisequence MR imaging: initial experience. , 2005, Radiology.

[67]  Erik Buskens,et al.  Imaging of carotid arteries in symptomatic patients: cost-effectiveness of diagnostic strategies. , 2004, Radiology.

[68]  Aaron Fenster,et al.  Measurement of Carotid Plaque Volume by 3-Dimensional Ultrasound , 2004, Stroke.

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

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

[71]  Daniel B. Russakoff,et al.  Intensity-based 2D-3D spine image registration incorporating a single fiducial marker. , 2005, Academic radiology.

[72]  Chun Yuan,et al.  Hemorrhage in the Atherosclerotic Carotid Plaque: A High-Resolution MRI Study , 2004, Stroke.

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

[74]  Savita Gupta,et al.  Medical ultrasound image compression using joint optimization of thresholding quantization and best-basis selection of wavelet packets , 2007, Digit. Signal Process..

[75]  Baohua Zhang,et al.  A review of algorithm research progress for non-rigid medical image registration , 2011, 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet).

[76]  Aaron Fenster,et al.  Nonrigid registration of three-dimensional ultrasound and magnetic resonance images of the carotid arteries. , 2009, Medical physics.

[77]  Alejandro F. Frangi,et al.  Three-dimensional modeling for functional analysis of cardiac images, a review , 2001, IEEE Transactions on Medical Imaging.

[78]  H. K. Abhyankar,et al.  Image Registration Techniques: An overview , 2009 .

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

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

[81]  Matthew D. Robson,et al.  Multicontrast MRI registration of carotid arteries in atherosclerotic and normal subjects , 2010, Medical Imaging.

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

[83]  Radhika Sivaramakrishna,et al.  Breast image registration techniques: a survey , 2006, Medical and Biological Engineering and Computing.

[84]  M. McConnell,et al.  Multicontrast black‐blood MRI of carotid arteries: Comparison between 1.5 and 3 tesla magnetic field strengths , 2006, Journal of magnetic resonance imaging : JMRI.