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  • MiMM_SBILab Dataset: Microscopic Images of Multiple Myeloma (MiMM_SBILab)


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Microscopic images were captured from bone marrow aspirate slides of patients diagnosed with multiple myeloma as per the standard guidelines. Slides were stained using Jenner- Giemsa stain. Images were captured at 1000x magnification using Nikon Eclipse-200 microscope equipped with a digital camera. Images were captured in raw BMP format with a size of 2560x1920 pixels. In all, this dataset consists of 85 images. All these 85 images were stain normalized using our in-house methodology before being used for segmentation. These stain normalized images have been provided as the annotated dataset with plasma cells marked in all image slides contained in a presentation for the ready reference of readers.

Additional Notes

This collection has also been uploaded to the Harvard Blood Cancer Dataverse website. Please refer to DOI 10.7910/DVN/XCX7ST for more information.

Additional Publications using this dataset:

  • Ritu Gupta, Pramit Mallick, Rahul Duggal, Anubha Gupta, and Ojaswa Sharma, "Stain Color Normalization and Segmentation of Plasma Cells in Microscopic Images as a Prelude to Development of Computer Assisted Automated Disease Diagnostic Tool in Multiple Myeloma," 16th International Myeloma Workshop (IMW), India, March 2017

Data Access

Data TypeDownload all or Query/FilterLicense
Slide Images (BMP, 1.27GB)

(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

Annotated plasma cell images (PDF, 12.67 MB)

Detailed Description

Image Statistics

Pathology Imaging Statistics



Number of Participants


Number of Studies


Number of Images


Images Size (GB)1.27

Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

Gupta, R., & Gupta, A. (2019). MiMM_SBILab Dataset: Microscopic Images of Multiple Myeloma [Data set]. The Cancer Imaging Archive.

Publication Citation

Gupta, A., Duggal, R., Gehlot, S., Gupta, R., Mangal, A., Kumar, L., Thakkar, N., & Satpathy, D. (2020). GCTI-SN: Geometry-inspired chemical and tissue invariant stain normalization of microscopic medical images. Medical Image Analysis, 65, 101788.

Publication Citation

Gupta, A., Mallick, P., Sharma, O., Gupta, R., & Duggal, R. (2018). PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma. PLOS ONE, 13(12), e0207908.

TCIA Citation

Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. Journal of Digital Imaging, 26(6), 1045–1057.

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.

Version 1 (Current): Updated 2019/03/25

Data TypeDownload all or Query/Filter
Images (BMP, 1.27GB)

    (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

Annotated plasma cell images (PDF)

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