Visual Analytics in Digital Pathology: Challenges and Opportunities

Abstract

The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.