Our Features


Mammography-machine independent

Thanks to our unique patented filtering feature that makes LIBCAD (and WEBCAD) mammography-machine agnostic. Regardless to the machine brand, resolution, or other technical features, all mammograms will be analyzed.

For all platforms

LIBCAD is offered in either a shared object for Linux, DLL for Windows, or API for cloud computations on our servers; all forms are programming-language independent. WEBCAD is offered as broweser-based interface that is OS-independent.

Full functionality

As opposed to some CADs that only provide markers, LIBCAD (and WEBCAD) produce several outputs, including: a heat-map probability image overlayed on the original mammogram, probability of malignancy, mass and micro-calcification detection, and unique filtering utilities.

Faster computation

LIBCAD's algorithms use hardware acceleration, and are parallelized on both CPU and GPU. These algorithms scale efficiently with processing power you have on your local machine. WEBCAD connects to LIBCAD installed on our servers, where we can provide a personalized computational power per user.

Easier integration

LIBCAD provides the simplest integration, enabling developers of SW companies to integrate to their imaging software. In addition, research centers can use it in their medical research, clinical trials, among others.

Rigorous research

Our research lab is committed to rigor, rather than ad hoc development. In addition, we are developing the new generation of CAD using novel techniques of deep nueral networks (DNN).


LIBCAD (and WEBCAD) has high sensitivity at a low false markers per image

Accuracy compared to U.S. commercial CADs

Integration of LIBCAD

is very simple and straightforward, with a little code snippet


  • Yousef, W. A. "Method and system for computer aided detection for cancer", Patent allowed, US 10,789,712, Sep., 2020.

  • Yousef, W. A., Ahmed A. Abouelkahire, Deyaaeldeen Almahallawi, Omar S.Marzouk, Sameh K. Mohamed, Waleed A. Mustafa, Omar M. Osama, Ali A. Saleh, Naglaa M. Abdelrazek (2019), "Method and System for Image Analysis to Detect Cancer", arXiv preprint arXiv:1908.10661

  • Abdel Razek, N. M., Yousef W. A., and W. A. Mustafa (2013). "Microcalcification detection with and without CAD system (LIBCAD): A comparative study." The Egyptian Journal of Radiology and Nuclear Medicine 44(2): 397-404.

  • Abdelrazek, N.; Yousef, W.; Mustafa, W. (2012), "Microcalcification detection with and without prototype CAD system (LIBCAD): a comparative study", European Society of Radiology (ECR 2012 / C-1063).

  • Yousef, W. A. et al. (2010), "On Detecting Abnormalities in Digital Mammography". in Applied Imagery Pattern Recognition Workshop 2010. Proceedings. 39th; IEEE Computer Society.