Transferable automatic hematological cell classification: Overcoming data limitations with self-supervised learning

CONCLUSIONS: The results demonstrate that SSL enables (1) extraction of meaningful cell image features without the use of cell class information; (2) efficient transfer of knowledge between bone marrow and peripheral blood cell domains; and (3) efficient model adaptation to new datasets using only a few labeled data …