his is a Matlab implementation of different tools for processing digital mammography images developed by Universidad Industrial de Santander. OpenBreast was publicly released in [1] and has been clinically evaluated for the task of breast cancer risk assessment in [2]. The following tasks have been implemented:
* Feature extraction for parenchymal analysis [1]
* Image standardization for (RAW and PROCESSED) digital mammography images
* Breast segmentation and chest wall detection [3]
* Detection of regions on interest within the breast [4,5]
* Breast density segmentation [6]
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
* demo05 Breast density segmentation
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] S. Pertuz et al., Clinical evaluation of a fully-automated parenchymal analysis software for breast cancer risk assessment: A pilot study in a Finnish sample,
European Journal of Radiology: 121, 2019.
[3] 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.
[4] S. Pertuz, C. Julia, D. Puig, A novel mammography image representation framework with application to image registration, Proc. International Conference on Pattern Recognition, 2014.
[5] G. Torres, S. Pertuz, Automatic Detection of the Retroareolar Region in Mammograms, Proc. Latin American Congress on Biomedical Engineering, 2016
[6] G. F. Torres et al., "Morphological Area Gradient: System-independent Dense Tissue Segmentation in Mammography Images," Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019.
引用格式
Said Pertuz (2024). OpenBreast (https://github.com/spertuz/openbreast), GitHub. 检索时间: .
S. Pertuz, G. F. Torres, R. Tamimi, J. Kamarainen, Open Framework for Mammography-based Breast Cancer Risk Assessment, IEEE-EMBS International Conference on Biomedical and Health Informatics, 2019
MATLAB 版本兼容性
平台兼容性
Windows macOS Linux类别
标签
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!demos
density
features
mapping
misc
mpatterns
segmentation
support/Inscribed_Rectangle
support/RAP__Risk_Assessment_Plot_
无法下载基于 GitHub 默认分支的版本
版本 | 已发布 | 发行说明 | |
---|---|---|---|
1.0.5 | - Included breast density segmentation |
|
|
1.0.0 |
|