Project Abstract: The development of high-quality digital scanners has made it possible to produce detailed images of hematoxylin and eosin (H&E) slides from cancer patient histological material. Emerging new informatics technologies also make it possible to develop machine learned models to extract additional important features from the digitized slides such as tumor infiltrating lymphocytes, delineating tumor regions and identifying nuclear segmentation. The Kentucky Cancer Registry’s Virtual Tissue Repository (VTR) has experience obtaining the H&E slides for specific patient populations from pathology labs across the state, having these slides digitized, submitting the anonymized digitized images to the National Cancer Institute (NCI) for research, and returning the original slides to the contributing pathology labs.