Fig. 5: Motion correction of in vivo mouse renal vascular imaging.

a The images show raw ULM images of a kidney arterial and venous renal tree acquired through 1 sec (first column) and 4 sec (second column) of DAQ time. The images are processed with SC (first row) and PSF-CC method (second row), respectively. SC-ULM image reconstructs renal vasculature within a respiratory cycle (~1 sec), and PSF-CC requires at least (3 respiratory, ~4 sec, to reconstruct a visible renal structure. The long DAQ time greatly degrades the image quality due to the motion. b Motion-induced frame-to-frame correlation changes during 4 sec of ultrasound image recording. The identified motions include respiratory and cardiac motions. c A representative in-plan motion within a 2D ultrasound image. The detectable in-plan motions contain lateral (solid black), axial (dotted black), and rotational (solid orange) components. d The comparison before and after applying out-of-plane (step 1) and in-plane (step 2) motion-correction algorithms to the PSF-CC ULM image. e The comparison of motion-corrected SC-ULM kidney images acquired with one breathing cycle of DAQ time and three breathing cycles of DAQ time. The insets show the zoom-in view of the renal vasculature trees. f The image similarity comparing SC-ULM images before and after the motion correction for one breathing cycle (~1 sec) and three breathing cycles (~4 sec). The center line in each box is the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. The whisker range is 5th to 95th percentiles. Scatter plots of the data used for the boxplot are overlaid on each boxplot. *p < 0.0001.