Annotation and characterization of lesions in breast tomosynthesis images.
Authors
Affiliations (5)
Affiliations (5)
- Translational Medicine, Diagnostic Radiology, Lund University, 205 02 Malmö, Sweden.
- Translational Medicine, Medical Radiation Physics, Lund University, 205 02 Malmö, Sweden.
- Department of Imaging and Physiology, Skåne University Hospital, 205 02 Malmö, Sweden.
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, 205 02 Malmö, Sweden.
- Department of Radiology, University of Pennsylvania, 3400 Spruce Str., Philadelphia, PA 19104, USA.
Abstract
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.