A level set framework with a shape and motion prior for segmentation and region tracking in echocardiography.
We describe a level set formulation using both shape and motion prior, for both segmentation and region tracking in high frame rate echocardiographic image sequences. The proposed approach uses the following steps: registration of the prior shape, level set segmentation constrained through the registered shape and region tracking. Registration of the prior shape is expressed as a rigid or an affine transform problem, where the transform minimizing a global region-based criterion is sought. This criterion is based on image statistics and on the available estimated axial motion data. The segmentation step is then formulated through front propagation, constrained with the registered shape prior. The same region-based criterion is used both for the registration and the segmentation step. Region tracking is based on the motion field estimated from the interframe level set evolution. The proposed approach is applied to high frame rate echocardiographic sequences acquired in vivo. In this particular application, the prior shape is provided by a medical expert and the rigid transform is used for registration. It is shown that this approach provides consistent results in terms of segmentation and stability through the cardiac cycle. In particular, a comparison indicates that the results provided by our approach are very close to the results obtained with manual tracking performed by an expert cardiologist on a Doppler Tissue Imaging (DTI) study. These preliminary results show the ability of the method to perform region tracking and its potential for dynamic parametric imaging of the heart.
Dydenko
Igor
I
CREATIS, UMR CNRS 5515, INSA, Bâtiment Blaise Pascal, 69621 Villeurbanne Cedex, France.
Jamal
Fadi
F
Bernard
Olivier
O
D'hooge
Jan
J
Magnin
Isabelle E
IE
Friboulet
Denis
D
D000465:Algorithms; D001185:Artificial Intelligence; D004452:Echocardiography / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique