Fig. 5: AI assisted quantitation of signal decay and local clearance of each contrast agent. | npj Imaging

Fig. 5: AI assisted quantitation of signal decay and local clearance of each contrast agent.

From: Tantalum oxide nanoparticles as versatile and high-resolution X-ray contrast agent for intraductal image-guided ablative procedure in rodent models of breast cancer

Fig. 5

A A deep learning algorithm was used to train gland segmentation using mask parameters defined by radiologists; Original, representative microCT image slices of contrast agent-injected mammary glands, radiologist-labeled segmentation masks per slice, AI prediction of segmentation masks per slice, automated AI segmentation result for image slice. B AI-assisted quantification of signal decay in short-term serial imaging characterization of indicated solutions (as shown in Fig. 1). C AI-assisted quantification of signal decay in long-term serial imaging characterization of indicated solutions (as shown in Figs. 3 and 4). Asterisks indicate p value of unpaired Welch’s t-test of stock compared to 70% EtOH solution of each contrast agent per time point (* <0.01, ** <0.001, *** <0.0001).

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