Abstract:

BACKGROUND: Tagged cardiac magnetic resonance imaging provides some information of cardiac boundary, which can be obtained by segmentation. However, the added tagging lines bring great difficult to accurate segmentation of the cardiac boundaries.
OBJECTIVE: Concerning the problem of segmentation of the left ventricle in tagged cardiac magnetic resonance (MR) images, a new method of automatic segmentation was proposed.
METHODS: Global histogram specification was firstly applied to improve contrast between tagged lines and untagged region. Afterwards, a simple method of texture analysis was adopted to discriminate ventricle blood-filled (untagged) and tagged (texture) regions. Bilateral filter was applied to filter off some block-like artifacts as well as to preserve the boundary of the left ventricle. Finally, GVF-snake model was utilized for automatically extracting the boundary of the left ventricle.
RESULTS AND CONCLUSION: A simple method based on texture analysis was proposed to remove the tagged lines: gray difference computed by subtracting the minimal from the maximal intensities within a local small window replaces the original gray value of a pixel; afterwards, filter off some block-like artifacts as well as preserve the boundary of the left ventricle by using bilateral filter; finally, the boundary of the left ventricle was extracted automatically based on GVF-snake model. Experimental results show that the proposed method can effectively extract the boundary of the left ventricle from tagged cardiac MR images.