Profile Norhene GARGOURI
First Name
Norhene
Last Name
GARGOURI
Address
Technopole of Sfax, PO Box 275, Sakiet Ezzit, 3021 Sfax - Tunisia
Zip code
3038
Biography
Dr. Norhène Gargouri Ben Ayed is an Associate Professor at the Digital Research Center of Sfax in Tunisia. She is a member of the SM@RT Laboratory and contributes to the Computers Imaging and Electronics Systems (CIELS) research team. Her research focuses on medical image processing, where she integrates advanced techniques such as deep learning, machine learning, and artificial neural networks.
Dr. Gargouri has authored over 25 scientific publications, with more than 260 citations. Her notable contributions include breast cancer anomaly detection using possibility theory and clustering paradigms, as well as the development of automatic breast computer-aided diagnosis (CAD) systems based on weighted feature fusion and deep convolutional neural networks.
In addition to her research activities, she serves as the President of the Association for Scientific Research (ABORS), reflecting her dedication to scientific advancement and collaboration.
Dr. Gargouri holds a Professional Doctorate in Engineering (PDEng) from the National Engineering School of Sfax, where she specialized in electrical engineering. She has also earned her University Habilitation, qualifying her to supervise doctoral research.
Research Interests
IA, Medical image processing
Scientific publications
| Title | Cited by | Year |
|---|---|---|
An automatic Computer-Aided Diagnosis system based on the Multimodal fusion of Breast Cancer (MF-CAD)R Mokni, N Gargouri, A Damak, D Sellami, W Feki, Z MnifBiomedical Signal Processing and Control 69, 102914, 2021 |
50 | 2021 |
A novel 3-D-CAD for breast and lesion segmentation of axial breast DCE-MRIF Besbes, N Gargouri, A Damak, W Feki, D Sellami, H Fourati, Z Mnif, ...Journal of Testing and Evaluation 49 (5), 3063-3080, 2021 |
4 | 2021 |
Combination of Texture and Shape Features Using Machine and Deep Learning Algorithms for Breast Cancer DiagnosisN Gargouri, R Mokni, A Damak, D Sellami, R Abid |
2 | 2021 |
Computer-Assisted Diagnosis System for Abnormalities Classification in Digital Mammography Based on Multi-Threshold Modified Local Ternary Pattern (MtMLTP)N Gargouri, M Zouari, R Boukhris, A Damak, D Sellami, S AmousJournal of Biomimetics, Biomaterials and Biomedical Engineering 49, 75-89, 2021 |
1 | 2021 |
A textural wavelet quantization approach for an efficient breast microcalcifcation’s detectionMZ Mehdi, NGB Ayed, AD Masmoudi, D SellamiMultimedia Tools and Applications 79 (33), 24911-24927, 2020 |
8 | 2020 |