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Ultrasound images are characterized by their speckle appearance, low contrast, and poor signal-to-noise ratio. It is always challenging to extract important clinical information from these images. An important step before automatic measurement is to transform the image into significant features of interest. Intensity based methods do not perform particularly well on ultrasound images. However, it has been shown previously that ultrasound images respond well to local phase-based methods which are theoretically intensity-invariant and thus suitable for low-contrast nature of ultrasound images. We extend the local phase-based method of feature asymmetry measure computation to detect 3D features using the monogenic signal, which is an isotropic extension of the analytic signal to higher dimensional functions. The proposed method is applied to real-time 3D echocardiography images and the visual results for the endocardial and epicardial boundary detection are presented.