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The advancement of biomedical research heavily relies on access to largeamounts of medical data. In the case of histopathology, Whole Slide Images(WSI) and clinicopathological information are valuable for developingArtificial Intelligence (AI) algorithms for Digital Pathology (DP).Transferring medical data "as open as possible" enhances the usability of thedata for secondary purposes but poses a risk to patient privacy. At the sametime, existing regulations push towards keeping medical data "as closed asnecessary" to avoid re-identification risks. Generally, these legal regulationsrequire the removal of sensitive data but do not consider the possibility ofdata linkage attacks due to modern image-matching algorithms. In addition, thelack of standardization in DP makes it harder to establish a single solutionfor all formats of WSIs. These challenges raise problems for bio-informaticsresearchers in balancing privacy and progress while developing AI algorithms.This paper explores the legal regulations and terminologies for medicaldata-sharing. We review existing approaches and highlight challenges from thehistopathological perspective. We also present a data-sharing guideline forhistological data to foster multidisciplinary research and education.

Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education