This is a Matlab implementation of different tools for processing digital mammography images developed by Universidad Industrial de Santander. The following tasks have been implemented [1]:
- Image standardization for (RAW and PROCESSED) digital mammography images
- Breast segmentation and chest wall detection [2]
- Detection of regions on interest within the breast [3,4]
- Feature extraction for parenchymal analysis [1]
To get started first run setup.m to configure Openbreast. Then run the following demos:
- demo01 Breast segmentation
- demo02 ST mapping
- demo03 ROI detection
- demo04 Feature extraction on FFDM images
For further details, please refer to: https://sites.google.com/view/cvia/openbreast
[1] S. Pertuz et al., Open Framework for Mammography-based Breast Cancer Risk Assessment, IEEE-EMBS International Conference on Biomedical and Health Informatics, 2019.
[2] B. Keller et al., Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation, Med. Phys, 2012.
[3] S. Pertuz, C. Julia, D. Puig, A novel mammography image representation framework with application to image registration, Proc. International Conference on Pattern Recognition, 2014.
[4] G. Torres, S. Pertuz, Automatic Detection of the Retroareolar Region in Mammograms, Proc. Latin American Congress on Biomedical Engineering, 2016