Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models

Synthetic bone marrow images augment real samples in developing acute myeloid leukemia microscopy classification models

Abstract High-quality image data is essential for training deep learning (DL) classifiers, yet data sharing is often limited by privacy concerns. We hypothesized that generative adversarial networks (GANs) could synthesize bone marrow smear (BMS) images suitable for classifier training. BMS from 125...

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Main Authors: Jan-Niklas Eckardt, Ishan Srivastava, Zizhe Wang, Susann Winter, Tim Schmittmann, Sebastian Riechert, Miriam Eva Helena Gediga, Anas Shekh Sulaiman, Martin M. K. Schneider, Freya Schulze, Christian Thiede, Katja Sockel, Frank Kroschinsky, Christoph Röllig, Martin Bornhäuser, Karsten Wendt, Jan Moritz Middeke
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01563-9
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https://doi.org/10.1038/s41746-025-01563-9

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