A deep learning approach for automatic recognition of abnormalities in the cytoplasm of neutrophils - Dataset
Description
This dataset contains digital images of neutrophils from peripheral blood smears used in the study titled "A deep learning approach for automatic recognition of abnormalities in the cytoplasm of neutrophils". The dataset includes 5605 images of neutrophils categorized into seven groups: Normal neutrophils (NEU), Hypogranulated neutrophils (HYP), neutrophils containing cryoglobulins (CRY), Döhle bodies (DB), Howell-Jolly body-like inclusions (HJBLI), green-blue inclusions of death (GBI), and phagocytosed bacteria (BAC). Note: This dataset is associated with the article "A deep learning approach for automatic recognition of abnormalities in the cytoplasm of neutrophils" by Kevin Barrera Llanga, José Rodellar, Santiago Alférez, and Anna Merino, published in Computers in Biology and Medicine. When using this data set, please cite the following article https://doi.org/10.1016/j.compbiomed.2024.108691
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Funding
Ministerio de Ciencia e Innovación
PDC2022-133514-I00