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The Cancer Imaging Archive

MiMM_SBILab | MiMM_SBILab Dataset: Microscopic Images of Multiple Myeloma

DOI: 10.7937/tcia.2019.pnn6aypl | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Bone Human 5 Histopathology Multiple Myeloma 1.28GB Image Analyses Public, Complete 2019/03/25


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.

Data Access

Version 1: Updated

Title Data Type Format Access Points Subjects Studies Series Images License
Slide Images Histopathology BMP
Download requires IBM-Aspera-Connect plugin
5 5 85 CC BY 3.0
Annotated plasma cell images PDF CC BY 3.0

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

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

Other Publications Using this Data

The following publications are recommended by the data submitters that may be useful to researchers utilizing this collection:

  • 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

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.

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. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC.