Literature DB >> 19291976

Nonrigid registration of three-dimensional ultrasound and magnetic resonance images of the carotid arteries.

Nuwan D Nanayakkara1, Bernard Chiu, Abbas Samani, J David Spence, Jagath Samarabandu, Grace Parraga, Aaron Fenster.   

Abstract

Atherosclerosis at the carotid bifurcation can result in cerebral emboli, which in turn can block the blood supply to the brain causing ischemic strokes. Noninvasive imaging tools that better characterize arterial wall, and atherosclerotic plaque structure and composition may help to determine the factors which lead to the development of unstable lesions, and identify patients at risk of plaque disruption and stroke. Carotid magnetic resonance (MR) imaging allows for the characterization of carotid vessel wall and plaque composition, the characterization of normal and pathological arterial wall, the quantification of plaque size, and the detection of plaque integrity. On the other hand, various ultrasound (US) measurements have also been used to quantify atherosclerosis, carotid stenosis, intima-media thickness, total plaque volume, total plaque area, and vessel wall volume. Combining the complementary information provided by 3D MR and US carotid images may lead to a better understanding of the underlying compositional and textural factors that define plaque and wall vulnerability, which may lead to better and more effective stroke prevention strategies and patient management. Combining these images requires nonrigid registration to correct the nonlinear misalignments caused by relative twisting and bending in the neck due to different head positions during the two image acquisition sessions. The high degree of freedom and large number of parameters associated with existing nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, high computational complexity, and low reliability. Thus, a "twisting and bending" model was used with only six parameters to model the normal movement of the neck for nonrigid registration. The registration technique was evaluated using 3D US and MR carotid images at two field strengths, 1.5 and 3.0 T, of the same subject acquired on the same day. The mean registration error between the segmented carotid artery wall boundaries in the target US image and the registered MR images was calculated using a distance-based error metric after applying a "twisting and bending" model based nonrigid registration algorithm. An average registration error of 1.4 +/- 0.3 mm was obtained for 1.5 T MR and 1.5 +/- 0.4 mm for 3.0 T MR, when registered with 3D US images using the nonrigid registration technique presented in this paper. Visual inspection of segmented vessel surfaces also showed a substantial improvement of alignment with this nonrigid registration technique compared to rigid registration.

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Year:  2009        PMID: 19291976     DOI: 10.1118/1.3056458

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  4 in total

1.  A hybrid framework for registration of carotid ultrasound images combining iconic and geometric features.

Authors:  Anupama Gupta; Harsh K Verma; Savita Gupta
Journal:  Med Biol Eng Comput       Date:  2013-05-25       Impact factor: 2.602

2.  The relationship between carotid intima-media thickness and carotid plaque in the Northern Manhattan Study.

Authors:  Tatjana Rundek; Hannah Gardener; David Della-Morte; Chuanhui Dong; Digna Cabral; Eduardo Tiozzo; Eugene Roberts; Milita Crisby; Kuen Cheung; Ryan Demmer; Mitchell S V Elkind; Ralph L Sacco; Moise Desvarieux
Journal:  Atherosclerosis       Date:  2015-06-03       Impact factor: 5.162

3.  Spatial registration of temporally separated whole breast 3D ultrasound images.

Authors:  Ganesh Narayanasamy; Gerald L LeCarpentier; Marilyn Roubidoux; J Brian Fowlkes; Anne F Schott; Paul L Carson
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

4.  A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP) Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration.

Authors:  Hengkai Guo; Guijin Wang; Lingyun Huang; Yuxin Hu; Chun Yuan; Rui Li; Xihai Zhao
Journal:  PLoS One       Date:  2016-02-16       Impact factor: 3.240

  4 in total

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