Fig. 2.

Exemplar vascular architectures generated in silico and processed through our photoacoustic image analysis pipeline. (A-C) XY maximum intensity projections of L-net vasculature. (A) Ground truth L-Net binary mask used to simulate raster-scanning optoacoustic mesoscopy (RSOM) image shown in (B, top) and subsequent optional vesselness filtering (VF) (B, bottom). (C) Segmented binary masks generated using either auto-thresholding (AT), auto-thresholding after vesselness filtering (AT + VF), random forest classification (RF); or random forest classification after vesselness filtering (RF+VF). (D) Segmented blood volume (BV) average across L-net image volumes, plotted against image volume depth (mm). For (D) n = 30 L-nets. See Supplementary Movie 1 for 3D visualisation.