Efficient nonlinear beamformer based on P'th root of detected signals for linear-array photoacoustic tomography: application to sentinel lymph node imaging.

Abstract

In linear-array transducer-based photoacoustic (PA) imaging, B-scan PA images are formed using the raw channel PA signals. Delay-and-sum (DAS) is the most prevalent algorithm due to its simple implementation, but it leads to low-quality images. Delay-multiply-and-sum (DMAS) provides a higher image quality in comparison with DAS while it imposes a computational burden of O ( M2 ) . We introduce a nonlinear (NL) beamformer for linear-array PA imaging, which uses the p'th root of the detected signals and imposes the complexity of DAS [O ( M ) ]. The proposed algorithm is evaluated numerically and experimentally [wire-target and in-vivo sentinel lymph node (SLN) imaging], and the effects of the parameter p are investigated. The results show that the NL algorithm, using a root of p (NL_p), leads to lower sidelobes and higher signal-to-noise ratio compared with DAS and DMAS, for (p > 2). The sidelobes level (for the wire-target phantom), at the depth of 11.4mm, are about -31, -52, -52, -67, -88, and -109 dB, for DAS, DMAS, NL_2, NL_3, NL_4, and NL_5, respectively, indicating the superiority of the NL_p algorithm. In addition, the best value of p for SLN imaging is reported to be 12.