Combining edge detection with speckle-tracking for cardiac strain assessment in 3D echocardiography

In this paper, we extend a computationally efficient framework for tracking of deformable subdivision surfaces in 3D echocardiography with speckle-tracking measurements to track material points. Tracking is performed in a sequential state-estimation fashion, using an extended Kalman filter to update a subdivision surface in a two-step process: Edge-detection is first performed to update the model for changes in shape and position, followed by a second update based on displacement vectors from speckle-tracking with 3D block-matching. The latter speckle-tracking update will only have to correct for residual deformations after edge-detection. This both leads to increased accuracy and computational efficiency compared to usage of speckle-tracking alone. Automatic tracking is demonstrated in a 3D echocardiography simulation of an infarcted ventricle. The combination of edge-detection and speckle-tracking consistently improved tracking accuracy (RMS 0.483, 0.433, 0.511 mm in X,Y,Z) compared to speckle-tracking alone (RMS 0.663, 0.439, 0.613 mm). It also improved the qualitative agreement for color-coded strain meshes to ground truth, and more clearly identified the infarcted region.