Gradient-driven beamforming for biomedical ultrasound

Abstract

Adaptive beamforming can significantly improve the image quality in biomedical ultrasound by reducing the clutter due to interfering signals arriving from undesired directions. We consider the conventional linearly constrained minimum variance (LCMV) adaptive beamformer and propose an alternative based on the well-known generalized sidelobe canceller (GSC) whose adaptation relies on unconstrained gradient-driven optimization. The GSC, coupled with iterative optimization methods, allows for a tradeoff between computational complexity of beamforming and the image quality. To the authors' knowledge, this is the first time a GSC-based gradient-driven approach has been applied and evaluated in the context of ultrasound beamforming.