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This technique does not require the use of exogenous contrast agents. The technique can be effectively used to realize endogenous and exogenous imaging of microvasculature. However, the depth of focus (DOF) realized using OR\u2010PAM is low and inadequate to cover the entire 3D data for microvasculature imaging. A varying extent of signal\u2010to\u2010noise ratio (SNR) is recorded when varying depths of the 3D sample are studied. This significantly hindered the processes of image recognition, segmentation, and analysis. Herein, a deep learning\u2010based OR\u2010PAM technique to image and analyze 3D datasets is proposed. Endogenous and exogenous multi\u2010organ imaging data are sequentially imaged and segmented, and excellent generalization ability is observed. Wide\u2010field and ultradense exogenous 3D imaging of mouse brain vasculature located at different depths is obtained and segmented by OR\u2010PAM for the first time. 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