Hosted by the School of Medicine at Cardiff University
Infrared spectroscopic imaging combines the ability to record molecular content with the ability to visualize chemistry in its spatial diversity. Recent advances in instrumentation make it possible to record high fidelity data in reasonable times, with insights ranging from cells in tissues to sub-cellular domains. We first describe a new microscope design for increased speed and rapid coverage that is useful for biomedical and clinical tissue imaging. We present several case studies of initial applications to samples in pathology. In each case, we show how emerging machine learning approaches can further augment these advances. We also discuss the merits of various techniques, trade-offs and potential directions. Finally, we present a new approach to nanoscale IR imaging that opens a new avenue for ultrastructural imaging of cells.
Rohit Bhargava is the Director of the Cancer Center at Illinois of the University of Illinois at Urbana-Champaign. Rohit is widely recognized for his research on chemical imaging and advances in theory, instrumentation, and applications in cancer pathology. Current work in chemical imaging in his laboratory focuses on theoretical modeling that can push the limits of speed and quality of infrared spectroscopic imaging as well as its application in several novel areas. In particular, Rohit’s group aims to recognize and subtype cancer by its underlying molecular characteristics, by advanced chemical imaging and application of modern machine learning, ultimately allowing for better treatment of patients. Using artificial intelligence techniques with IR imaging, his recent work is focused on understanding and using the native molecular content of the tumor and its microenvironment for improved cancer pathology.