Interest in quantitative image analysis and visualization in healthcare, from population-level academic research studies to patient-specific analysis has grown precipitously in the recent past. While the application of these tools for large-scale research have found significant support from the research community developing these tools, opportunities at smaller scale, especially at the clinical level where most healthcare effort and research is executed, have been extremely limited. Tools appropriate at the population scale are generally inaccessible to these communities, while their potential value has exploded. Interest and awareness of these tools has never been higher, as physicians and researchers have recognized how HPC and visualization can complement and even drive their own work. Lines of communication between these intersecting fields, however, have been extremely limited, stifling engagement and deployment of the most advanced imaging analysis and technology for healthcare research and clinical practice.

Our goal is to bring together the communities of engineers, mathematicians, and research scientists together with medical and clinical professionals including surgeons, radiologists and clinically-facing researchers to identify and work towards solutions that face the medical image analysis and visualization community. Our workshop is the first of its kind at SC specifically focused on the issues facing medical and clinical professionals. While extremely advanced image analysis and visualization techniques have been developed over the past decade, their adoption, while of clear utility for pre-operative planning and research purposes, has been limited to all but the most advanced joint development projects without broad community adoption at the patient-focused level. We will use this collaborative workshop to specifically address the needs of both communities, especially focusing on the practice of image analysis and segmentation in healthcare, and the specific workflow and technical requirements required.