Early prostate cancer detection in MRI
- The Classification Power of Classical and Intra-voxel Incoherent Motion (IVIM) Fitting Models of Diffusion-weighted Magnetic Resonance Images: An Experimental Study.Journal of Digital Imaging, 35(3), pp.678-691.Alkadi, R., Abdullah, O. and Werghi, N., 2022. [pdf] [demo]
- Diffusion-weighted MRI based System for the Early Detection of Prostate Cancer Alkadi, R., Werghi, N., Shalaby, A., Taher, F., El-Baz, A. [pdf] [demo]
- Early diagnosis and staging of prostate cancer using magnetic resonance imaging: State of the art and perspectives Alkadi, R., Taher, F., El-Baz, A., Werghi, N. [pdf] [demo]
- A deep learning-based approach for the detection and localization of prostate cancer in T2 magnetic resonance images Alkadi, R., Taher, F., El-Baz, A., Werghi, N. [pdf] [demo]
- A 2.5 D deep learning-based approach for prostate cancer detection on T2-weighted magnetic resonance imaging Alkadi, R., Taher, F., El-Baz, A., Werghi, N. [pdf] [demo]
- A comprehensive non-invasive framework for diagnosing prostate cancer Reda, I., Shalaby, A., Elmogy, M., Abou Elfotouh, A., Khalifa, F., Abou El-Ghar, M., Hosseini-Asl, E., Gimel'farb, G., Werghi, N. and El-Baz, A. [pdf] [demo]
- Computer-aided diagnostic tool for early detection of prostate cancer Reda, I., Shalaby, A., Khalifa, F., Elmogy, M., Aboulfotouh, A., Abou El-Ghar, M., Hosseini-Asl, E., Werghi, N., Keynton, R. and El-Baz, A. [pdf] [demo]
Detection and Classification of abdominal aortic aneurysm in CT
- Segmentation of abdominal aortic aneurysm (AAA) based on topology prior model Salahat, S., Soliman, A., McGloughlin, T., Werghi, N., and El-Baz, A. In Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017, Edinburgh, UK, July 11–13, 2017, Proceedings 21 (pp. 219-228). Springer International Publishing. [pdf] [demo]
- Detection of calcification from abdominal aortic aneurysm Salahat, S., Soliman, A., Bhaskar, H., McGloughlin, T., El-Baz, A., and Werghi, N. Cardiovascular Imaging and Image Analysis, pp. 173-196. [pdf] [demo]