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BONE-MARROW-CYTOMORPHOLOGY_MLL_HELMHOLTZ_FRAUNHOFER - The Cancer Imaging Archive (TCIA)
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BONE-MARROW-CYTOMORPHOLOGY_MLL_HELMHOLTZ_FRAUNHOFER


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The Cancer Imaging Archive

Bone-Marrow-Cytomorphology_MLL_Helmholtz_Fraunhofer | An Expert-Annotated Dataset of Bone Marrow Cytology in Hematologic Malignancies

DOI: 10.7937/TCIA.AXH3-T579 | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Status Updated
Marrow Human 945 Histopathology Leukemia & Lymphoma Cancers 6.8GB Public, Complete 2021/11/12

Summary

The dataset contains a collection of over 170,000 de-identified, expert-annotated cells from the bone marrow smears of 945 patients stained using the May-Grünwald-Giemsa/Pappenheim stain. The diagnosis distribution in the cohort included a variety of hematological diseases reflective of the sample entry of a large laboratory specialized in leukemia diagnostics. Image acquisition was performed using a brightfield microscope with 40x magnification and oil immersion.

Large datasets with a high quality of both data acquisition and annotation are key prerequisites to develop data-driven, computational methods in diagnostic medicine. In the case of bone marrow morphology, a key diagnostic method for a broad range of hematologic diseases, only few datasets are publicly available so far, which are orders of magnitude smaller than the one presented here. Inclusion of our dataset into TCIA provides both medical researchers and bioinformaticians with a public resource for education and algorithm improvement.

All samples were processed in the Munich Leukemia Laboratory (MLL), scanned using equipment developed at Fraunhofer IIS and post-processed using software developed at Helmholtz Munich.

Data Access

Version 1: Updated 2021/11/12

Title Data Type Format Access Points Subjects Studies Series Images License
Tissue Slide Images Histopathology JPG
Download requires IBM-Aspera-Connect plugin
945 171,375 CC BY 4.0
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Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

Data Citation

Matek, C., Krappe, S., Münzenmayer, C., Haferlach, T., & Marr, C. (2021). An Expert-Annotated Dataset of Bone Marrow Cytology in Hematologic Malignancies [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.AXH3-T579

Detailed Description

Abbreviations:

ABE Abnormal eosinophil
ART Artefact
BAS Basophil
BLA Blast
EBO Erythroblast
EOS Eosinophil
FGC Faggott cell
HAC Hairy cell
KSC Smudge cell
LYI Immature lymphocyte
LYT Lymphocyte
MMZ Metamyelocyte
MON Monocyte
MYB Myelocyte
NGB Band neutrophil
NGS Segmented neutrophil
NIF Not identifiable
OTH Other cell
PEB Proerythroblast
PLM Plasma cell
PMO Promyelocyte

Acknowledgements

  • Christian Matek and Carsten Marr acknowledge support from the German National Research foundation (DFG) through grant SFB 1243.
  • Carsten Marr has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement number 866411).

Related Publications

Publications by the Dataset Authors

The authors recommended this paper as the best source of additional information about this dataset:

  • Matek, C., Krappe, S., Münzenmayer, C., Haferlach, T., and Marr, C. (2021). Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image dataset. https://doi.org/10.1182/blood.2020010568

No publications by dataset authors were found.

Publication Citation

Matek, C., Krappe, S., Münzenmayer, C., Haferlach, T., and Marr, C. (2021). Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image dataset. https://doi.org/10.1182/blood.2020010568

Research Community Publications

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.

Other Publications Using this Data

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you’d like to add please contact TCIA’s Helpdesk.