Hiba Mzoughi
Orcid: 0000-0002-2664-9962
According to our database1,
Hiba Mzoughi
authored at least 17 papers
between 2018 and 2025.
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Bibliography
2025
Deep learning based computer aided diagnosis (CAD) tool supported by explainable artificial intelligence for breast cancer exploration.
Appl. Intell., May, 2025
Vision transformers (ViT) and deep convolutional neural network (D-CNN)-based models for MRI brain primary tumors images multi-classification supported by explainable artificial intelligence (XAI).
Vis. Comput., March, 2025
Biomed. Signal Process. Control., 2025
Computer Aided Diagnosis CAD tool for lung and thoracic pathologies detection from chest X-ray images.
Proceedings of the International Wireless Communications and Mobile Computing, 2025
Proceedings of the 22nd IEEE International Multi-Conference on Systems, Signals & Devices, 2025
2024
Proceedings of the 7th IEEE International Conference on Advanced Technologies, 2024
Review of MRI brain tumor segmentation and MGMT promoter classification methods on BraTs dataset based on Deep learning.
Proceedings of the 7th IEEE International Conference on Advanced Technologies, 2024
2023
Deep efficient-nets with transfer learning assisted detection of COVID-19 using chest X-ray radiology imaging.
Multim. Tools Appl., October, 2023
Deep Transfer Learning (DTL) Based-Framework for an Accurate Multi-classification of MRI Brain Tumors.
Proceedings of the International Conference on Cyberworlds, 2023
Proceedings of the International Conference on Cyberworlds, 2023
2022
Computer Aided Diagnosis (CAD) tool for MS lesions exploration In multimodal brain MRI.
Proceedings of the 6th International Conference on Advanced Technologies for Signal and Image Processing, 2022
Review of Computer Aided-Diagnosis (CAD) Systems for MRI Gliomas brain tumors explorations based on Machine Learning and Deep learning.
Proceedings of the 6th International Conference on Advanced Technologies for Signal and Image Processing, 2022
2021
Towards a computer aided diagnosis (CAD) for brain MRI glioblastomas tumor exploration based on a deep convolutional neuronal networks (D-CNN) architectures.
Multim. Tools Appl., 2021
Medical Biol. Eng. Comput., 2021
2020
Deep Multi-Scale 3D Convolutional Neural Network (CNN) for MRI Gliomas Brain Tumor Classification.
J. Digit. Imaging, 2020
Glioblastomas brain Tumor Segmentation using Optimized U-Net based on Deep Fully Convolutional Networks (D-FCNs).
Proceedings of the 5th International Conference on Advanced Technologies for Signal and Image Processing, 2020
2018
Histogram equalization-based techniques for contrast enhancement of MRI brain Glioma tumor images: Comparative study.
Proceedings of the 4th International Conference on Advanced Technologies for Signal and Image Processing, 2018