Window-Based Plane Wave Ultrasound Beamforming With Efficient Angle Selection

Plane wave (PW) ultrasound imaging achieves ultrafast frame rates by insonifying the entire field of view with wide-angle plane waves and coherently compounding echoes across multiple transmission angles. However, acquiring and processing a large number of angles imposes significant computational and storage burdens, especially in real-time systems. To address this, we propose a two-fold framework that jointly optimizes beamforming and angle selection. First, we introduce a Weighted Window-based Beamforming (WBF) algorithm that adaptively emphasizes regions of interest using smooth window functions, thereby improving local contrast and mitigating artifacts from angle undersampling. Second, we propose a Queue-based Angle Selection Algorithm (QASA) that sequentially identifies the most informative transmission angles while maintaining balanced angular coverage. Experiments on PICMUS datasets demonstrate that WBF combined with QASA achieves image quality comparable to conventional delay-and-sum compounding with all 75 angles, while using only 15 angles—a reduction of 80%. This enables higher frame rates, reduced data acquisition, and lower computational overhead without compromising image fidelity.