One of the most demanding tasks in state-of-the-art medical ultrasound systems is the localization of possible scatterers in the body based on received echoes. Digital beamforming involves the summation of all received echoes in each image point according to their time of flight, i.e., their delay. This requires the knowledge of the delays for all combinations of ultrasound transmitters, image points and receivers. Recent three-dimensional (3D) systems comprise thousands of transducer elements and millions of image points. Compared to traditional 2D systems, the total number of delays is several orders of magnitude larger. In this paper, we present a new beamforming algorithm that exploitsthe inherent locality in the image formation and efficiently approximates the delays. Compared to latest proposed architectures, this results in 20 percent less arithmetic operations, and a reduction of the input/output (I/O) bandwidth and the total memory size by factors of 30 and 50, respectively.
Efficient parallel beamforming for 3D ultrasound imaging / Vogel, Pirmin; Bartolini, Andrea; Benini, Luca. - STAMPA. - (2014), pp. 175-180. (Intervento presentato al convegno 24th Great Lakes Symposium on VLSI, GLSVLSI 2014 tenutosi a Houston, TX, usa nel 2014) [10.1145/2591513.2591599].
Efficient parallel beamforming for 3D ultrasound imaging
BARTOLINI, ANDREA;BENINI, LUCA
2014
Abstract
One of the most demanding tasks in state-of-the-art medical ultrasound systems is the localization of possible scatterers in the body based on received echoes. Digital beamforming involves the summation of all received echoes in each image point according to their time of flight, i.e., their delay. This requires the knowledge of the delays for all combinations of ultrasound transmitters, image points and receivers. Recent three-dimensional (3D) systems comprise thousands of transducer elements and millions of image points. Compared to traditional 2D systems, the total number of delays is several orders of magnitude larger. In this paper, we present a new beamforming algorithm that exploitsthe inherent locality in the image formation and efficiently approximates the delays. Compared to latest proposed architectures, this results in 20 percent less arithmetic operations, and a reduction of the input/output (I/O) bandwidth and the total memory size by factors of 30 and 50, respectively.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.