Three-dimensional automatic volume registration of carotid MR images

We created an automatic three-dimensional registration algorithm for magnetic resonance images of carotid vessels. Potential applications include atherosclerotic plaque characterization and plaque burden quantification vector-based segmentation using dark blood MR images having multiple contrast weightings (proton density (PD), T1, and T2). Another application is measurement of disease progression and regression with drug trials. We used mutual information registration algorithm to compensate movements between image acquisitions. PD, T1, and T2 images were acquired from patients and volunteers and then matched for image analysis. Visualization methods such as contour overlap showed that vessels well aligned after registration. Distance measurements from the landmarks indicated that the registration method worked well with an error of 1.09 /spl plusmn/ 0.42 mm.

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

[2]  Guy Marchal,et al.  Multi-modality image registration by maximization of mutual information , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

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

[4]  Hervé Delingette,et al.  Automatic Detection and Segmentation of Evolving Processes in 3D Medical Images: Application to Multiple Sclerosis , 1999, IPMI.

[5]  David L Wilson,et al.  A comparative study of warping and rigid body registration for the prostate and pelvic MR volumes. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[6]  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.

[7]  David L. Wilson,et al.  Automatic MR volume registration and its evaluation for the pelvis and prostate. , 2002, Physics in medicine and biology.

[8]  Paul M. Matthews,et al.  Monitoring disease activity and progression in primary progressive multiple sclerosis using MRI: sub-voxel registration to identify lesion changes and to detect cerebral atrophy , 2002, Journal of Neurology.

[9]  W M O'Fallon,et al.  Ischemic stroke subtypes : a population-based study of functional outcome, survival, and recurrence. , 2000, Stroke.

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

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