Recent developments in deep learning have enabled data-driven algorithms that can reach
human-level performance and beyond. The development and deployment of medical image
analysis methods have several challenges, including data heterogeneity due to population
diversity and different device manufacturers. In addition, more input from experts is required
for a reliable method development process. While the exponential growth in clinical imaging
data has enabled deep learning to flourish, data heterogeneity, multi-modality, and rare or …