This dataset consists of 361 whole slide images (WSI) - 296 malignant from women with invasive breast cancer (HER2 neg) and 65 benign. The tumours have been classified with four SNOMED-CT categories based on morphology: invasive duct carcinoma, invasive lobular carcinoma, in situ carcinoma, and others. 4144 separate annotations have been made to segment different tissue structures connected to ontologies.

Keywords: Pathology, Breast, Cancer, Whole slide imaging, Annotated.

Sample images

Sample images with reduced image quality. Please click to preview.

Dataset information

Short name DRBR
Cite as Anna Bodén, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler (2019) Breast data from the Visual Sweden project DROID doi:10.23698/aida/drbr
Field Pathology
Organ Breast
Age span
Title Breast data from the Visual Sweden project DROID
Author Anna Bodén
Jerónimo F. Rose
Martin Lindvall
Caroline Bivik Stadler
Year 2019
DOI doi:10.23698/aida/drbr
Status Completed
Version 1.1.0
Scans 361
Annotations 4144
Size 500.8GB
Resolution 40X single plane, scanned in NDP format
Modality SM
Scanner Hamamatsu NanoZoomer-XR C12000 series 2013
Hamamatsu NanoZoomer 2.0 HT C9600 series 2013
Stain H&E (hematoxylin and eosin)
Phase
References
  1. Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. J Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4
Access
constraints

Controlled access
Free for use in legal and ethical medical diagnostics research.
Please contact the copyright holder for terms of access.

AIDA BY license
Free for use within AIDA with attribution.

Copyright Copyright 2019 Linköping University, Claes Lundström
Download Please contact Anna Bodén, Claes Lundstrom, or Joel Hedlund to request access.

Annotation

The breast tumours were classified with four SNOMED-CT categories based on morphology: invasive duct carcinoma, Invasive lobular carcinoma, in situ carcinoma and others. 4144 separate annotations were made to segment different tissue structures connected to ontologies. One physician were responsible for the manual annotations controlled by a second pathologist.

License

Controlled access

Free for use in legal and ethical medical diagnostics research. Please contact the copyright holder for terms of access.

AIDA BY license

Copyright 2019 Linköping University, Claes Lundström

Permission to use, copy, modify, and/or distribute this data within Analytic Imaging Diagnostics Arena (AIDA) for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies, and that publications resulting from the use of this data cite the following works:

Anna Bodén, Jerónimo F. Rose, Martin Lindvall, and Caroline Bivik Stadler (2019) Breast data from the Visual Sweden project DROID doi:10.23698/aida/drbr.

Stadler, C.B., Lindvall, M., Lundström, C. et al. Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. J Digit Imaging (2020). https://doi.org/10.1007/s10278-020-00384-4

THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS DATA.