Tracking the left ventricle in ultrasound images based on total variation denoising

Tracking the Left Ventricle (LV) in ultrasound sequences remains a challenge due to speckle noise, low SNR and lack of contrast. Therefore, it is usually difficult to obtain accurate estimates of the LV cavities since feature detectors produce a large number of outliers. This paper presents an algorithm which combines two main operations: i) a novel denoising algorithm based on the Lyapounov equation and ii) a robust tracker, based on an outlier feature model. Experimental results are provided, showing that the proposed algorithm is computationally efficient and leads to accurate estimates of the LV.