The invention relates to the technical field of optical
microscopic imaging, in particular to a wide-view-field multi-
photon microscopic imaging method, device and equipment, and the method comprises the steps: obtaining training data collected by a multi-
photon microscope according to a rolling sub-sampling scanning strategy, the strategy covers the entire
field of view by successively and longitudinally moving a periodic scan path of
high frame rate, low spatial sampling rate. Preprocessing such as normalization,
time sequence registration or space division is carried out on the data, and a
mask matrix is generated; and performing cross supervision by using the complementary region to construct a self-
supervised training sample and a pseudo tag. And training a three-dimensional
convolutional neural network based on the training samples and the pseudo labels, and performing reasoning reconstruction on the rolling sub-sampling data by using the trained network to obtain a target
image sequence. Therefore, the problem that in the prior art, the high spatial sampling density causes the low
frame rate, and the
high frame rate needs the small imaging area or the low spatial sampling rate, that is, the imaging view field and the imaging temporal-spatial resolution are difficult to consider at the same time is solved.