{"id":2972,"date":"2011-06-24T19:49:29","date_gmt":"2011-06-24T19:49:29","guid":{"rendered":"https:\/\/mtlsites.mit.edu\/annual_reports\/2011\/?p=2972"},"modified":"2011-07-19T18:54:06","modified_gmt":"2011-07-19T18:54:06","slug":"digital-processing-and-beamforming-for-portable-medical-ultrasound-imaging-2","status":"publish","type":"post","link":"https:\/\/mtlsites.mit.edu\/annual_reports\/2011\/digital-processing-and-beamforming-for-portable-medical-ultrasound-imaging-2\/","title":{"rendered":"Digital Processing and Beamforming for Portable Medical Ultrasound Imaging"},"content":{"rendered":"

An ultrasound image is formed from a collection of ultrasonic beams transmitted and received by an array of transducer elements.\u00a0 As the resolution of an image and the range over which an image is to be formed increase, so do the number of these transducer elements and the corresponding digital processing units.\u00a0 The intensive signal processing power required for ultrasound imaging [1<\/a>] <\/sup> means that conventional ultrasound systems are often large and expensive, and this demand for processing power can only worsen as more transducers and signal channels are implemented.\u00a0 Three-dimensional (3D) ultrasound images, composed of a set of adjacently acquired two-dimensional images, are formed using two-dimensional (2D) transducer arrays [2<\/a>] <\/sup>.\u00a0 This further increases the signal processing requirement: if a one-dimensional (1D) array of N transducers costs a complexity of N, the corresponding 3D image would require a complexity of N2<\/sup>.\u00a0 Countering these trends is the movement to smaller form-factors for portable ultrasound systems that are less operator-dependent, warranting the use of advanced algorithms and architectures for back-end digital processing.\u00a0 Figure 1 illustrates a simplified block diagram of a typical ultrasound system.<\/p>\n

Beamforming, which in its simplest form involves delaying, scaling, and summing to produce a coherent signal from the collection of received beams, has been identified as an area for algorithmic research and development [3<\/a>] <\/sup>.\u00a0 Figure 2 shows a schematic describing the delay-and-sum operation.\u00a0 This work explores advanced beamforming techniques with an efficient and low-power hardware implementation in mind. Specifically, synthetic apertures and adaptive beamforming are implemented to reduce the number of channels and the data rate required for image formation.\u00a0 The power and area reduction in a low-power implementation of the beamformer are demonstrated.<\/p>\n\n\t\t