Ultrasound is a popular imaging modality for investigating soft-tissue structures within the body. Unlike other medical imaging modalities, e.g. CT and SPECT, ultrasound does not utilize ionizing radiation and is therefore a preferable diagnostic modality. In addition, it provides the user with imaging and quantitative information concerning the blood flow. Ultrasound is the only non-invasive medical imaging modality that acquires true real-time images, thus allowing imaging of dynamic structure like the heart, and allows monitoring during treatment.

In order to generate an image, ultrasound systems must interrogate the tissue by emitting narrow beams to different directions. In order to transmit and receive narrow beams and orient them, multiple electro-acoustic transducers are used. The data acquired by the electro-acoustic array, has traditionally been processed by means of spatial filtering, also called beamforming, to obtain an image of the scattering objects. The classical time-domain Delay-And-Sum (DAS) method is usually used, which is analogous to the operation of an acoustical lens and can be performed efficiently in real time using delay-line operations, or using post-processing as in synthetic aperture systems. Conventional beamforming, though, has several drawbacks. Mainly, DAS beamformer has relatively high side-lobe level that translates to poor contrast. By using aperture shading, the side-lobe level of the beam profile can be significantly reduced but the main-lobe gets enlarged, resulting in increased contrast at the expense of resolution. Moreover, off-axis scatterers can introduce clutter, reducing the overall quality of the obtained data.

In contrast to the predetermined shading in DAS, adaptive beamformers use the recorded wavefield to compute the aperture weights. By suppressing interfering signals from off-axis directions and allowing large side-lobes in directions from which no signal energy is received, the adaptive beamformers can increase resolution. Adaptive beamforming algorithms have been extensively studied and implemented for applications such as passive SONAR, RADAR, or seismology. However, few studies have directly addressed the application of adaptive beamforming to ultrasound imaging.

In this work, we survey and compare state-of-the-art adaptive beamforming methods that specifically address issues related to diagnostic ultrasound imaging.  As a background, this work includes a survey of general beamforming techniques such as synthetic aperture and multi-line acquisition methods; but the main purpose of this work is to study ultrasound adaptive beamforming techniques.