Abstract：
:Magnetic resonance (MR) tagging has been shown to be a useful technique for noninvasively measuring the deformation of an in vivo heart. An important step in analyzing tagged images is the identification of tag lines in each image of a cine sequence. Most existing tag identification algorithms require user defined myocardial contours. Contour identification, however, is time consuming and requires a considerable amount of user intervention. In this paper, a new method for identifying tag lines, which we call the ML/MAP method, is presented that does not require user defined myocardial contours. The ML/MAP method is composed of three stages. First, a set of candidate tag line centers is estimated across the entire region-of-interest (ROI) with a snake algorithm based on a maximum-likelihood (ML) estimate of the tag center. Next, a maximum a posteriori (MAP) hypothesis test is used to detect the candidate tag centers that are actually part of a tag line. Finally, a pruning algorithm is used to remove any detected tag line centers that do not meet a spatio-temporal continuity criterion. The ML/MAP method is demonstrated on data from ten in vivo human hearts.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Denney TS Jrdoi
10.1109/42.768842subject
Has Abstractpub_date
1999-04-01 00:00:00pages
330-44issue
4eissn
0278-0062issn
1558-254Xjournal_volume
18pub_type
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