Digitization of the imaging diagnostics in pathology has the potential to increase both efficiency and quality of care. In order to realize this potential, cross-disciplinary research efforts are needed that can combine clinical expertise with knowledge in artificial intelligence and human-computer interaction.
Ground Truth for AI Models
The CMIV research agenda in digital pathology tackles several image analysis challenges. An important groundwork is to create systematically annotated collections of imaging data to be used as ground truth for training of artificial intelligence models. Applications include correlating findings between radiology and histology in liver biopsies and increasing precision and efficiency in breast cancer histological grading. Furthermore, the possibilities to validate the clinical work are investigated and human-computer interaction aspects are explored. A common ground for the research projects is the focus on finding digital solutions that will work in the clinical setting. A special track is an effort where visualization challenges for 3D histology are being addressed, in particular handling of the very large data sets at interactive speed.
The CMIV pathology group consists both of medical and technical researchers from the university and pathologists and lab assistants from the clinical pathology department at the hospital, all working together on research and development efforts close to clinical practice. The group also organizes the annual Nordic Symposium on Digital Pathology.