Sophia Zackrisson
Manager
Annotation and characterization of lesions in breast tomosynthesis images
Author
Summary, in English
Rapid adoption of artificial intelligence methods in breast imaging research emphasizes the need for large, appropriately curated image databases for development and validation. For digital breast tomosynthesis (DBT), there are few public databases with only limited lesion annotation. Recently, we have developed Malmö Breast ImaginG (M-BIG), a large database of 104 791 women screened at Skåne University Hospital, Malmö. M-BIG also includes all images from the Malmö Breast Tomosynthesis Screening Trial, MBTST of 14 848 women, with 139 biopsy-confirmed cancers from DBT screening. To annotate lesions in M-BIG, we designed a semi-automated custom software tool for DBT, and corresponding digital mammography (DM) images. A reader manually draws an outline; or marks nodes around the lesion which are automatically connected by an edge-following algorithm. Our custom tool enables detailed annotation of DBT and DM lesions, as opposed to the rectangular regions present in other published material, allowing extensive evaluation of tumor segmentation, and analysis of size and shape descriptors.
Department/s
- LUCC: Lund University Cancer Centre
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
- Lund Laser Centre, LLC
- LU Profile Area: Light and Materials
- LTH Profile Area: Photon Science and Technology
- EpiHealth: Epidemiology for Health
- Medical Radiation Physics, Lund
Publishing year
2026-03-01
Language
English
Pages
326-330
Publication/Series
Radiation Protection Dosimetry
Volume
202
Issue
3-4
Document type
Journal article
Publisher
Oxford University Press
Topic
- Radiology and Medical Imaging
Status
Published
Research group
- Radiology Diagnostics, Malmö
- Medical Radiation Physics, Malmö
ISBN/ISSN/Other
- ISSN: 0144-8420