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We recently have developed a stand-alone single-impulse photoacoustic computed tomography (SIP-PACT) system, which integrates high spatiotemporal resolution, deep penetration, and full-view fidelity, as well as anatomical, dynamic, and functional contrasts. To better reveal detailed features inside the body, we developed a half-time dual-speed-of-sound (dual-sos) universal back-projection algorithm to compensate for the first-order effect of acoustic inhomogeneity. However, the previous dual-sos reconstruction method requires human intervention for reconstruction parameter tuning. Later, we developed a smart reconstruction via machine learning, it can produce almost the same quality images anatomically. By localizing single-dyed droplets, the spatial resolution of SIP-PACT has been improved by six-fold in vivo but compromising the temporal resolution. Deep-learning accelerates the droplet localization process, improving the temporal resolution by almost 20-fold.
Lei Li (Wed,) studied this question.