Hardware Acceleration of Beamforming in a UWB Imaging Unit for Breast Cancer Detection

The Ultrawideband (UWB) imaging technique for breast cancer detection is based on the fact that cancerous cells have different dielectric characteristics than healthy tissues. When a UWB pulse in the microwave range strikes a cancerous region, the reflected signal is more intense than the backscatter originating from the surrounding fat tissue. A UWB imaging system consists of transmitters, receivers, and antennas for the RF part, and of a digital back-end for processing the received signals. In this paper we focus on the imaging unit, which elaborates the acquired data and produces 2D or 3D maps of reflected energies. We show that one of the processing tasks, Beamforming, is the most timing critical and cannot be executed in software by a standard microprocessor in a reasonable time. We thus propose a specialized hardware accelerator for it. We design the accelerator in VHDL and test it in an FPGA-based prototype. We also evaluate its performance when implemented on a CMOS 45nm ASIC technology. The speed-up with respect to a software implementation is on the order of tens to hundreds, depending on the degree of parallelism permitted by the target technology.

[1]  Xu Li,et al.  Microwave imaging via space-time beamforming for early detection of breast cancer , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  A. Taflove,et al.  Three-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: design of an antenna-array element , 1999 .

[3]  D. W. van der Weide,et al.  Microwave imaging via space-time beamforming: experimental investigation of tumor detection in multilayer breast phantoms , 2004, IEEE Transactions on Microwave Theory and Techniques.

[4]  A. Taflove,et al.  Two-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: fixed-focus and antenna-array sensors , 1998, IEEE Transactions on Biomedical Engineering.

[5]  Gianluca Piccinini,et al.  UDSM Trends Comparison: From Technology Roadmap to UltraSparc Niagara2 , 2012, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[6]  Mariagrazia Graziano,et al.  A flexible UWB Transmitter for breast cancer detection imaging systems , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

[7]  B.D. Van Veen,et al.  An overview of ultra-wideband microwave imaging via space-time beamforming for early-stage breast-cancer detection , 2005, IEEE Antennas and Propagation Magazine.

[8]  Mariagrazia Graziano,et al.  A Fully Differential Digital CMOS UWB Pulse Generator , 2009, Circuits Syst. Signal Process..

[9]  Mariagrazia Graziano,et al.  A VHDL-AMS Simulation Environment for an UWB Impulse Radio Transceiver , 2008, IEEE Transactions on Circuits and Systems I: Regular Papers.

[10]  S. K. Davis,et al.  MICROWAVE IMAGING VIA SPACE-TIME BEAMFORMING FOR EARLY DETECTION OF BREAST CANCER: BEAMFORMER DESIGN IN THE FREQUENCY DOMAIN , 2003 .

[11]  Massimo Ruo Roch,et al.  MEDEA: a hybrid shared-memory/message-passing multiprocessor NoC-based architecture , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

[12]  Massimo Ruo Roch,et al.  A NoC-based hybrid message-passing/shared-memory approach to CMP design , 2011, Microprocess. Microsystems.

[13]  Mariagrazia Graziano,et al.  A mixed-signal demodulator for a low-complexity IR-UWB receiver: Methodology, simulation and design , 2009, Integr..

[14]  S.C. Hagness,et al.  A confocal microwave imaging algorithm for breast cancer detection , 2001, IEEE Microwave and Wireless Components Letters.