Publications

Journal Publications

  • Khawaled, S. and Freiman, M., 2022. NPBDREG: Uncertainty Assessment in Diffeomorphic Brain MRI Registration using a Non-parametric Bayesian Deep-Learning Based Approach. Computerized Medical Imaging and Graphics, p.102087.
  • Khawaled, S. and Freiman, M., NPB-REC: A Non-parametric Bayesian Deep-learning Approach for Undersampled MRI Reconstruction with Uncertainty Estimation, will be published Artificial Intelligence In Medicine, Elsevier.
  • Fichmann Levital, M., Khawaled, S., John A. K and Freiman, M., Non-parametric Bayesian Deep Learning Approach for Whole-Body Low-Dose PET Reconstruction and Uncertainty Assessment, submitted

Conference Publications

  • Khawaled, S., Khateeb, M., & Benisty, H. (2018, December). Audio Retrieval By Voice Imitation. In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE) (pp. 1-4). IEEE.‏
  • Khawaled, S., Zachevsky, I., & Zeevi, Y. Y. J. (2018, December). Analysis of Piecewise Fractional Brownian Motion Signals and Textures. In 2018 IEEE International Conference on the Science of Electrical Engineering in Israel (ICSEE) (pp. 1-5). IEEE.‏
  • Khawaled, S., & Zeevi, Y. Y. (2019, September). Fractal Features Combined with Local Phase Information in Texture Analysis. In 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA) (pp. 234-239). IEEE.‏
  • Dar Arava, Mohammad Masarwy, Samah Khawaled, and Moti Freiman. “Deep Learning-based Motion Correction for Myocardial T1 Mapping.” In the Proceedings of the 2021 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS). †

† Won the European Microwave Association (EuMA) Award.

  • Khawaled, S. and Freiman, M., 2022. NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data. In International Workshop on Machine Learning for Medical Image Reconstruction (pp. 14-23). Springer, Cham
  • Fichmann Levital, M., Khawaled, S., John A. K and Freiman, M., Uncertainty Assessment in Whole-Body Low Dose Pet Reconstruction Using Non-Parametric Bayesian Deep Learning Approach, to appear in the proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI) 2023

Selected Lectures and Talks 

  • On the Interplay of Structure and Texture in Natural Images, Tel Aviv, Israel, Israel Machine Vision Conference (IMVC) 2019
  • Fractal Features Combined with Local Phase Information in Texture Analysis, Oral Presentation, Dubrovnik, Croatia, International Symposium on Image and Signal Processing and Analysis (ISPA) 2019
  • The Valedictory Speech for M.Sc. Graduation Ceremony, The
    Virtual M.Sc. Graduation event, 30 Sep. 2020
  • NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data, Oral Power Pitch presentation, ISMRM, Toronto Canada, June 2023.

Selected Projects

  • Improving Transfer Learning for Breast Cancer*  (Joint work with Sheraz Faraj, Project Web), Haifa, Israel, The Israeli Medical and Biological Engineering Society (ISMBE) Meeting 2020
    * Won the Thomas Schwartz Prize, awarded to undergraduate projects in Image and Signal Processing
  • Stochastic Textures Modeling and Its Application in Texture Structure Decomposition Project Web 

M.Sc. Thesis project, with Prof. Zeevi