title: Compound Radar Approach for Breast Imaging.
abstract: Multistatic radar apertures record scattering at a number of receivers when the target is illuminated by a single transmitter, providing more scattering information than its monostatic counterpart per transmission angle. This paper considers the well-known problem of detecting tumor targets within breast phantoms using multistatic radar. To accurately image potentially cancerous targets size within the breast, a significant number of multistatic channels are required in order to adequately calibrate-out unwanted skin reflections, increase the immunity to clutter, and increase the dynamic range of a breast radar imaging system. However, increasing the density of antennas within a physical array is inevitably limited by the geometry of the antenna elements designed to operate with biological tissues at microwave frequencies. A novel compound imaging approach is presented to overcome these physical constraints and improve the imaging capabilities of a multistatic radar imaging modality for breast scanning applications. The number of transmit-receive (TX-RX) paths available for imaging are increased by performing a number of breast scans with varying array positions. A skin calibration method is presented to reduce the influence of skin reflections from each channel. Calibrated signals are applied to receive a beamforming method, compounding the data from each scan to produce a microwave radar breast profile. The proposed imaging method is evaluated with experimental data obtained from constructed phantoms of varying complexity, skin contour asymmetries, and challenging tumor positions and sizes. For each imaging scenario outlined in this study, the proposed compound imaging technique improves skin calibration, clearly detects small targets, and substantially reduces the level of undesirable clutter within the profile.
authors.forename: Dallan
authors.initials: D
authors.lastname: Byrne
authors.forename: Mantalena
authors.initials: M
authors.lastname: Sarafianou
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Craddock
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008872:Microwaves; D019047:Phantoms, Imaging; D011825:Radar / Q000295:instrumentation*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity