With increasing demand to correlate data across multiple imaging modalities, Race and colleagues demonstrate a mechanism by which annotations can be generated on images from one imaging modality and transferred to a second image modality for data integration (and optionally, back again). Further, they perform this workflow on mass spectrometry images of a pancreatic cancer mouse model and hematoxylin and eosin-stained sections. HALO and HALO AI image analysis software was used to develop a DenseNet algorithm to classify and generate annotations for pancreatic ductal carcinoma tumor, non-neoplastic acinar tissue, and connective tissue on H&E-stained slides. This method for bidirectional transfer of image annotations may enable novel workflows in the future.