Chinese Optics Letters, 2016, 14 (9): 091701, Published Online: Aug. 3, 2018
Sparse photoacoustic microscopy based on low-rank matrix approximation Download: 1153次
Abstract
As a high-resulotion biological imaging technology, photoacoustic microscopy (PAM) is difficult to use in real-time imaging due to the long data acquisition time. Herein, a fast data acquisition and image recovery method named sparse PAM based on a low-rank matrix approximation is proposed. Specifically, the process to recover the final image from incomplete data is formulated into a low-rank matrix completion framework, and the “Go Decomposition” algorithm is utilized to solve the problem. Finally, both simulated and real PAM experiments are conducted to verify the performance of the proposed method and demonstrate clinical potential for many biological diseases.
Ting Liu, Mingjian Sun, Naizhang Feng, Minghua Wang, Deying Chen, Yi Shen. Sparse photoacoustic microscopy based on low-rank matrix approximation[J]. Chinese Optics Letters, 2016, 14(9): 091701.