Parallelization Strategy for Elementary Morphological Operators on Graphs. - Imane Youkana; Jean Cousty; Rachida Saouli; Mohamed Akil (DGCI, 2016)

Parallelization Strategy for Elementary Morphological Operators on Graphs: Distance-Based Algorithms and Implementation on Multicore Shared-Memory Architecture. - Imane Youkana; Jean Cousty; Rachida Saouli; Mohamed Akil (J. Math. Imaging Vis., 2017)

Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images. - Mostefa Ben Naceur; Rachida Saouli; Mohamed Akil; Rostom Kachouri (Comput. Methods Programs Biomed., 2018)

Deep Convolutional Neural Networks for Brain Tumor Segmentation: Boosting Performance Using Deep Transfer Learning: Preliminary Results. - Mostefa Ben Naceur; Mohamed Akil; Rachida Saouli; Rostom Kachouri (BrainLes@MICCAI (2), 2019)

A New Online Class-Weighting Approach with Deep Neural Networks for Image Segmentation of Highly Unbalanced Glioblastoma Tumors. - Mostefa Ben Naceur; Rostom Kachouri; Mohamed Akil; Rachida Saouli (IWANN (2), 2019)

Combined Datasets For Breast Cancer Grading Based On Multi-CNN Architectures. - Adel Abdelli; Rachida Saouli; Khalifa Djemal; Imane Youkana (IPTA, 2020)

Synthetic medical image generator for data augmentation and anonymisation based on generative adversarial network for glioblastoma tumors growth prediction. - Adel Kamli; Rachida Saouli; Hadj Batatia; Mostefa Bennaceur; Imane Youkana (IET Image Process., 2020)

Left ventricular segmentation based on a parallel watershed transformation towards an accurate heart function evaluation. - Ramzi Mahmoudi; Narjes Ben Ameur; Asma Ammari; Mohamed Akil; Rachida Saouli; Badii Hmida; Mohamed Hedi Bedoui (IET Image Process., 2020)

Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy. - Mostefa Ben Naceur; Mohamed Akil; Rachida Saouli; Rostom Kachouri (Medical Image Anal., 2020)

Slice-Level-Guided Convolutional Neural Networks to study the Right Ventricular Segmentation using MRI Short-Axis sequences. - Asma Ammari; Ramzi Mahmoudi; Badii Hmida; Rachida Saouli; Mohamed Hedi Bedoui (AICCSA, 2021)

A review of approaches investigated for right ventricular segmentation using short-axis cardiac MRI. - Asma Ammari; Ramzi Mahmoudi; Badii Hmida; Rachida Saouli; Mohamed Hédi Bedoui (IET Image Process., 2021)

Analysis of Right Ventricle Segmentation in the End Diastolic and End Systolic Cardiac Phases Using UNet-Based Models. - Rania Mabrouk; Ramzi Mahmoudi; Asma Ammari; Rachida Saouli; Mohamed Hedi Bedoui (ICCCI (CCIS Volume), 2022)

Fully Integrated Spatial Information to Improve FCM Algorithm for Brain MRI Image Segmentation. - Fouzia Chighoub; Rachida Saouli (Autom. Control. Comput. Sci., 2022)

Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network. - Adel Abdelli; Rachida Saouli; Khalifa Djemal; Imane Youkana (Int. J. Imaging Syst. Technol., 2022)

Clinical-Guided Strategy Towards a Spatio-Temporal Cardiac MRI Right Ventricular Short-Axis (ST-CMRI-RVSA) Labeled Dataset. - Asma Ammari; Ramzi Mahmoudi; Badii Hmida; Mezri Maatouk; Rachida Saouli; Mohamed Hédi Bedoui (SN Comput. Sci., 2022)

Deep-active-learning approach towards accurate right ventricular segmentation using a two-level uncertainty estimation. - Asma Ammari; Ramzi Mahmoudi; Badii Hmida; Rachida Saouli; Mohamed Hedi Bedoui (Comput. Medical Imaging Graph., 2023)