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.
© 2016 Chinese Laser Press
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