TY - GEN
T1 - Simultaneous reconstruction of 4-D myocardial motion from both tagged and untagged MR images using nonrigid image registration
AU - Shi, Wenzhe
AU - Murgasova, Maria
AU - Edwards, Philip
AU - Rueckert, Daniel
PY - 2010
Y1 - 2010
N2 - Tagged magnetic resonance (MR) imaging is unique in its ability to noninvasively image the motion and deformation of the heart. However, it is difficult to identify and quantify structures of interest in the cardiac anatomy since the tags obscure the anatomy. In this paper, we present a novel and fully automated technique based on nonrigid image registration for the analysis of myocardial motion using both tagged and untagged MR images. The novel aspect of our technique is its simultaneous usage of complementary information from both tagged and untagged images. No manual intervention is required to obtain the segmentation of the end-diastolic images. To estimate the motion within the myocardium, we register a sequence of images taken during systole to a set of reference images taken at end-diastole, maximizing a spatial weighted similarity measure between the images. We use short-axis and long-axis images of the heart as well as tagged and untagged images to estimate a fully four-dimensional motion field within the myocardium. We have evaluated the proposed approach on 8 patients both in terms of robustness, accuracy and consistency of the motion tracking. The proposed method is significantly more consistent than motion tracking on tagged MR images only.
AB - Tagged magnetic resonance (MR) imaging is unique in its ability to noninvasively image the motion and deformation of the heart. However, it is difficult to identify and quantify structures of interest in the cardiac anatomy since the tags obscure the anatomy. In this paper, we present a novel and fully automated technique based on nonrigid image registration for the analysis of myocardial motion using both tagged and untagged MR images. The novel aspect of our technique is its simultaneous usage of complementary information from both tagged and untagged images. No manual intervention is required to obtain the segmentation of the end-diastolic images. To estimate the motion within the myocardium, we register a sequence of images taken during systole to a set of reference images taken at end-diastole, maximizing a spatial weighted similarity measure between the images. We use short-axis and long-axis images of the heart as well as tagged and untagged images to estimate a fully four-dimensional motion field within the myocardium. We have evaluated the proposed approach on 8 patients both in terms of robustness, accuracy and consistency of the motion tracking. The proposed method is significantly more consistent than motion tracking on tagged MR images only.
UR - http://www.scopus.com/inward/record.url?scp=78049432276&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15699-1_11
DO - 10.1007/978-3-642-15699-1_11
M3 - Conference contribution
AN - SCOPUS:78049432276
SN - 3642156983
SN - 9783642156984
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 98
EP - 107
BT - Medical Imaging and Augmented Reality - 5th International Workshop, MIAR 2010, Proceedings
T2 - 5th International Workshop on Medical Imaging and Augmented Reality, MIAR 2010
Y2 - 19 September 2010 through 20 September 2010
ER -