Improved Lesion Detection Using Nonlocal Means Post-Processing

Software beamforming allows more flexible and complex algorithms, often referred to as adaptive beamforming techniques, that are blurring the boundaries between beamforming and image processing. Many adaptive beamforming algorithms claim to improve lesion detectability. Based on recent advances, we hypothesize that image processing techniques that reduce speckle variability yield better lesion detectability than state-of-the-art adaptive beamformers. This hypothesis is investigated on six algorithms: two image processing techniques, and four adaptive beamformers. As a target we use Field II simulations of a hypoechoic cyst with noise added to simulate different SNR conditions. Lesion detectability is estimated using the Generalized Contrast-to-Noise Ratio (GCNR). The results support our hypothesis.