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Based on photoacoustic effect, photoacoustic tomography is developing veryfast in recent years, and becoming an important imaging tool for bothpreclinical and clinical studies. With enough ultrasound transducers placedaround the biological tissue, PAT can provide both deep penetration and highimage contrast by hybrid usage of light and sound. However, considering spaceand measurement environmental limitations, transducers are always placed in alimited-angle way, which means that the other side without transducer coveragesuffers severe information loss. With conventional image reconstructionalgorithms, the limited-view tissue induces artifacts and information loss,which may cause doctors misdiagnosis or missed diagnosis. In order to solvelimited-view PA imaging reconstruction problem, we propose to use both timedomain and frequency domain reconstruction algorithms to get delay-and-sum(DAS) image inputs and k-space image inputs. These dual domain images sharenearly same texture information but different artifact information, which canteach network how to distinguish these two kinds of information at input level.In this paper, we propose Dual Domain Unet (DuDoUnet) with specially designedInformation Sharing Block (ISB), which can further share two domains'information and distinguish artifacts. Besides, we use mutual information (MI)with an auxiliary network, whose inputs and outputs are both ground truth, tocompensate prior knowledge of limited-view PA inputs. The proposed method isverified with a public clinical database, and shows superior results with SSIM= 93.5622% and PSNR = 20.8859.

Limited-view Photoacoustic Imaging Reconstruction With Dual Domain Inputs Under Mutual Information Constraint