Re-identification from histopathology images

arXiv:2403.12816v1 Announce Type: new
Abstract: In numerous studies, deep learning algorithms have proven their potential for the analysis of histopathology images, for example, for revealing the subtypes of tumors or the primary origin of metastases. These models require large datasets for training, which must be anonymized to prevent possible patient identity leaks. This study demonstrates that even relatively simple deep learning algorithms can re-identify patients in large histopathology datasets with substantial accuracy. We evaluated our algorithms on two TCIA datasets …

abstract algorithms analysis arxiv cs.ai cs.cv datasets deep learning deep learning algorithms example identification identity images large datasets leaks patient studies study training tumors type