Publication: Evaluation of deep learning training strategies for the classification of bone marrow cell images
Evaluation of deep learning training strategies for the classification of bone marrow cell images
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Glüge, S., Balabanov, S., Koelzer, V. H., & Ott, T. (2023). Evaluation of deep learning training strategies for the classification of bone marrow cell images. Computer Methods and Programs in Biomedicine, 243, 107924. https://doi.org/10.1016/j.cmpb.2023.107924
Abstract
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Abstract
BACKGROUND AND OBJECTIVE
The classification of bone marrow (BM) cells by light microscopy is an important cornerstone of hematological diagnosis, performed thousands of times a day by highly trained specialists in laboratories worldwide. As the manual evaluation of blood or BM smears is very time-consuming and prone to inter-observer variation, new reliable automated systems are needed.
METHODS
We aim to improve the automatic classification performance of hematological cell types. Therefore, we evaluate four state-of-the-art Convol
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Creators (Authors)
- Glüge, Stefan
- Balabanov, Stefan
- Ott, Thomas
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Glüge, S., Balabanov, S., Koelzer, V. H., & Ott, T. (2023). Evaluation of deep learning training strategies for the classification of bone marrow cell images. Computer Methods and Programs in Biomedicine, 243, 107924. https://doi.org/10.1016/j.cmpb.2023.107924
