Rachida Saouli
Orcid: 0000-0002-4299-2664
According to our database1,
Rachida Saouli
authored at least 16 papers
between 2016 and 2023.
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Bibliography
2023
Deep-active-learning approach towards accurate right ventricular segmentation using a two-level uncertainty estimation.
Comput. Medical Imaging Graph., March, 2023
2022
Clinical-Guided Strategy Towards a Spatio-Temporal Cardiac MRI Right Ventricular Short-Axis (ST-CMRI-RVSA) Labeled Dataset.
SN Comput. Sci., 2022
Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network.
Int. J. Imaging Syst. Technol., 2022
Fully Integrated Spatial Information to Improve FCM Algorithm for Brain MRI Image Segmentation.
Autom. Control. Comput. Sci., 2022
Analysis of Right Ventricle Segmentation in the End Diastolic and End Systolic Cardiac Phases Using UNet-Based Models.
Proceedings of the Advances in Computational Collective Intelligence, 2022
2021
A review of approaches investigated for right ventricular segmentation using short-axis cardiac MRI.
IET Image Process., 2021
Slice-Level-Guided Convolutional Neural Networks to study the Right Ventricular Segmentation using MRI Short-Axis sequences.
Proceedings of the 18th IEEE/ACS International Conference on Computer Systems and Applications, 2021
2020
Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.
Medical Image Anal., 2020
Left ventricular segmentation based on a parallel watershed transformation towards an accurate heart function evaluation.
IET Image Process., 2020
Synthetic medical image generator for data augmentation and anonymisation based on generative adversarial network for glioblastoma tumors growth prediction.
IET Image Process., 2020
Proceedings of the Tenth International Conference on Image Processing Theory, 2020
2019
A New Online Class-Weighting Approach with Deep Neural Networks for Image Segmentation of Highly Unbalanced Glioblastoma Tumors.
Proceedings of the Advances in Computational Intelligence, 2019
Deep Convolutional Neural Networks for Brain Tumor Segmentation: Boosting Performance Using Deep Transfer Learning: Preliminary Results.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images.
Comput. Methods Programs Biomed., 2018
2017
Parallelization Strategy for Elementary Morphological Operators on Graphs: Distance-Based Algorithms and Implementation on Multicore Shared-Memory Architecture.
J. Math. Imaging Vis., 2017
2016
Proceedings of the Discrete Geometry for Computer Imagery, 2016